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提交
7105962f
编写于
12月 01, 2016
作者:
T
Tao Luo
提交者:
GitHub
12月 01, 2016
浏览文件
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差异文件
Merge pull request #636 from wangyang59/unifyConv
Unify conv
上级
98f4c761
09a5b8bd
变更
11
隐藏空白更改
内联
并排
Showing
11 changed file
with
303 addition
and
20 deletion
+303
-20
paddle/gserver/layers/ConvProjection.cpp
paddle/gserver/layers/ConvProjection.cpp
+4
-3
paddle/gserver/layers/ExpandConvBaseLayer.cpp
paddle/gserver/layers/ExpandConvBaseLayer.cpp
+6
-6
paddle/gserver/tests/CMakeLists.txt
paddle/gserver/tests/CMakeLists.txt
+7
-0
paddle/gserver/tests/img_conv_a.conf
paddle/gserver/tests/img_conv_a.conf
+2
-1
paddle/gserver/tests/img_conv_b.conf
paddle/gserver/tests/img_conv_b.conf
+1
-1
paddle/gserver/tests/img_conv_c.conf
paddle/gserver/tests/img_conv_c.conf
+43
-0
paddle/gserver/tests/test_ConvUnify.cpp
paddle/gserver/tests/test_ConvUnify.cpp
+199
-0
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+11
-5
paddle/gserver/tests/test_NetworkCompare.cpp
paddle/gserver/tests/test_NetworkCompare.cpp
+10
-0
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+2
-1
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+18
-3
未找到文件。
paddle/gserver/layers/ConvProjection.cpp
浏览文件 @
7105962f
...
...
@@ -59,7 +59,8 @@ void ConvProjection::getConvParams() {
void
ConvProjection
::
initCudnn
()
{
hl_create_filter_descriptor
(
&
filterDesc_
,
channels_
,
numFilters_
,
filterH_
,
filterW_
);
&
filterDesc_
,
channels_
/
groups_
,
numFilters_
/
groups_
,
filterH_
,
filterW_
);
hl_create_tensor_descriptor
(
&
inputDesc_
);
hl_create_tensor_descriptor
(
&
outputDesc_
);
hl_create_convolution_descriptor
(
&
convDesc_
,
...
...
@@ -86,7 +87,7 @@ void ConvProjection::initCudnn() {
void
ConvProjection
::
reshapeTensorDesc
(
int
batchSize
)
{
hl_tensor_reshape
(
inputDesc_
,
batchSize
,
channels_
,
channels_
/
groups_
,
imageH_
,
imageW_
,
channels_
*
imageH_
*
imageW_
,
...
...
@@ -115,7 +116,7 @@ void ConvProjection::reshapeTensorDesc(int batchSize) {
hl_tensor_reshape
(
outputDesc_
,
batchSize
,
numFilters_
,
numFilters_
/
groups_
,
outputH_
,
outputW_
,
nStride
,
...
...
paddle/gserver/layers/ExpandConvBaseLayer.cpp
浏览文件 @
7105962f
...
...
@@ -145,7 +145,7 @@ void ExpandConvBaseLayer::expandFwdOnce(MatrixPtr image,
real
*
expInData
=
expandInput_
->
getData
();
for
(
int
g
=
0
;
g
<
groups_
[
inIdx
];
++
g
)
{
MatrixPtr
A
=
Matrix
::
create
(
wgtData
,
sub
K
,
subM
,
tru
e
,
useGpu_
);
// mark transpose
Matrix
::
create
(
wgtData
,
sub
M
,
subK
,
fals
e
,
useGpu_
);
// mark transpose
MatrixPtr
B
=
Matrix
::
create
(
expInData
,
subK
,
subN
,
false
,
useGpu_
);
MatrixPtr
C
=
Matrix
::
create
(
outData
,
subM
,
subN
,
false
,
useGpu_
);
C
->
mul
(
A
,
B
,
1
,
1
);
...
...
@@ -182,7 +182,7 @@ void ExpandConvBaseLayer::bpropActs(MatrixPtr out,
// create temporary matrix
MatrixPtr
C
=
Matrix
::
create
(
expandInData
,
subK
,
subN
,
false
,
useGpu_
);
MatrixPtr
B
=
Matrix
::
create
(
localGradData
,
subM
,
subN
,
false
,
useGpu_
);
MatrixPtr
A
=
Matrix
::
create
(
wgtData
,
sub
K
,
subM
,
fals
e
,
useGpu_
);
MatrixPtr
A
=
Matrix
::
create
(
wgtData
,
sub
M
,
subK
,
tru
e
,
useGpu_
);
C
->
mul
(
A
,
B
);
// mul
// clear the temporary matrix
...
...
@@ -247,10 +247,10 @@ void ExpandConvBaseLayer::bpropWeights(MatrixPtr image,
// expand-mul one-group by one
for
(
int
g
=
0
;
g
<
groups_
[
inpIdx
];
g
++
)
{
MatrixPtr
A
=
Matrix
::
create
(
expandInData
,
subK
,
subN
,
fals
e
,
useGpu_
);
MatrixPtr
B
=
Matrix
::
create
(
gradData
,
subM
,
subN
,
tru
e
,
useGpu_
);
MatrixPtr
C
=
Matrix
::
create
(
wGradData
,
sub
K
,
subM
,
false
,
useGpu_
);
C
->
mul
(
A
,
B
,
1
,
1
);
MatrixPtr
A
=
Matrix
::
create
(
expandInData
,
subK
,
subN
,
tru
e
,
useGpu_
);
MatrixPtr
B
=
Matrix
::
create
(
gradData
,
subM
,
subN
,
fals
e
,
useGpu_
);
MatrixPtr
C
=
Matrix
::
create
(
wGradData
,
sub
M
,
subK
,
false
,
useGpu_
);
C
->
mul
(
B
,
A
,
1
,
1
);
A
->
clear
();
B
->
clear
();
...
...
paddle/gserver/tests/CMakeLists.txt
浏览文件 @
7105962f
...
...
@@ -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/img_conv_a.conf
浏览文件 @
7105962f
...
...
@@ -34,6 +34,7 @@ conv = img_conv_layer(input=data, filter_size=1, filter_size_y=1,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
True
,
act
=
LinearActivation
())
act
=
LinearActivation
(),
groups
=
2
)
outputs
(
concat
,
conv
)
paddle/gserver/tests/img_conv_b.conf
浏览文件 @
7105962f
...
...
@@ -24,7 +24,7 @@ proj2 = conv_projection(input=data, filter_size=1, filter_size_y=1,
concat
=
concat_layer
(
input
=[
proj1
,
proj2
],
bias_attr
=
False
,
act
=
ReluActivation
())
proj
=
conv_projection
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
)
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
groups
=
2
)
with
mixed_layer
(
bias_attr
=
True
,
act
=
LinearActivation
())
as
conv
:
conv
+=
proj
...
...
paddle/gserver/tests/img_conv_c.conf
0 → 100644
浏览文件 @
7105962f
#edit-mode: -*- python -*-
# Copyright (c) 2016 Baidu, Inc. 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.
from
paddle
.
trainer_config_helpers
import
*
settings
(
batch_size
=
10
)
data
=
data_layer
(
name
=
"input"
,
size
=
8
*
16
*
16
)
conv1
=
img_conv_layer
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
False
,
act
=
ReluActivation
(),
layer_type
=
"exconv"
)
conv2
=
img_conv_layer
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
False
,
act
=
ReluActivation
(),
layer_type
=
"exconv"
)
concat
=
concat_layer
(
input
=[
conv1
,
conv2
])
conv
=
img_conv_layer
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
True
,
act
=
LinearActivation
(),
groups
=
2
,
layer_type
=
"exconv"
)
outputs
(
concat
,
conv
)
paddle/gserver/tests/test_ConvUnify.cpp
0 → 100644
浏览文件 @
7105962f
/* 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
,
size_t
groups
,
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
);
size_t
weightSize
=
channel
*
filter_size
*
filter_size
*
config
.
layerConfig
.
num_filters
()
/
groups
;
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_0"
,
imgSize
*
imgSize
*
channel
,
weightSize
});
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
(
groups
);
conv
->
set_filter_channels
(
channel
/
groups
);
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
,
weightSize
);
convLayer
->
forward
(
PASS_GC
);
return
convLayer
->
getOutputValue
();
}
TEST
(
Layer
,
convParaUnified
)
{
#ifndef PADDLE_ONLY_CPU
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
,
/*groups*/
1
,
input
,
param
,
false
);
resultGpu
=
doOneConvTest
(
/* imgSize */
4
,
/* output_x */
2
,
/* stride */
1
,
/* padding */
0
,
/* filter_size */
3
,
/*channel*/
1
,
/*numfilters*/
2
,
/*groups*/
1
,
input
,
param
,
true
);
checkMatrixEqual
(
resultCpu
,
resultGpu
);
input
=
Matrix
::
create
(
1
,
3
*
3
*
2
,
false
,
false
);
float
inputData2
[]
=
{
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
9
,
10
,
11
,
12
,
13
,
14
,
15
,
16
,
17
,
18
};
float
param2
[]
=
{
1
,
2
,
3
,
4
,
5
,
6
,
7
,
8
,
8
,
7
,
6
,
5
,
4
,
3
,
2
,
1
};
input
->
setData
(
inputData2
);
resultCpu
=
doOneConvTest
(
/* imgSize */
3
,
/* output_x */
2
,
/* stride */
1
,
/* padding */
0
,
/* filter_size */
2
,
/*channel*/
2
,
/*numfilters*/
2
,
/*groups*/
1
,
input
,
param2
,
false
);
resultGpu
=
doOneConvTest
(
/* imgSize */
3
,
/* output_x */
2
,
/* stride */
1
,
/* padding */
0
,
/* filter_size */
2
,
/*channel*/
2
,
/*numfilters*/
2
,
/*groups*/
1
,
input
,
param2
,
true
);
checkMatrixEqual
(
resultCpu
,
resultGpu
);
float
param3
[]
=
{
1
,
2
,
3
,
4
,
4
,
3
,
2
,
1
};
resultCpu
=
doOneConvTest
(
/* imgSize */
3
,
/* output_x */
2
,
/* stride */
1
,
/* padding */
0
,
/* filter_size */
2
,
/*channel*/
2
,
/*numfilters*/
2
,
/*groups*/
2
,
input
,
param3
,
false
);
resultGpu
=
doOneConvTest
(
/* imgSize */
3
,
/* output_x */
2
,
/* stride */
1
,
/* padding */
0
,
/* filter_size */
2
,
/*channel*/
2
,
/*numfilters*/
2
,
/*groups*/
2
,
input
,
param3
,
true
);
checkMatrixEqual
(
resultCpu
,
resultGpu
);
#endif
}
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
();
}
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
7105962f
...
...
@@ -166,9 +166,8 @@ TEST(Projection, scaling) {
}
}
#ifndef PADDLE_ONLY_CPU
TEST
(
Projection
,
conv
)
{
const
int
NUM_FILTERS
=
16
;
void
testProjectionConv
(
size_t
groups
)
{
const
int
NUM_FILTERS
=
18
;
const
int
FILTER_SIZE
=
2
;
const
int
FILTER_SIZE_Y
=
3
;
const
int
CHANNELS
=
3
;
...
...
@@ -186,7 +185,7 @@ TEST(Projection, conv) {
conv
->
set_padding_y
(
1
);
conv
->
set_stride
(
2
);
conv
->
set_stride_y
(
2
);
conv
->
set_groups
(
1
);
conv
->
set_groups
(
groups
);
conv
->
set_filter_channels
(
conv
->
channels
()
/
conv
->
groups
());
conv
->
set_img_size
(
IMAGE_SIZE
);
int
output_x
=
outputSize
(
conv
->
img_size
(),
...
...
@@ -206,13 +205,20 @@ TEST(Projection, conv) {
testProjectionGrad
(
conf
,
INPUT_DATA
,
/* parameterSize */
NUM_FILTERS
*
CHANNELS
*
FILTER_SIZE
*
FILTER_SIZE_Y
,
/* parameterSize */
NUM_FILTERS
*
CHANNELS
*
FILTER_SIZE
*
FILTER_SIZE_Y
/
groups
,
/* batchSize */
100
,
true
,
false
,
NUM_FILTERS
,
true
);
}
#ifndef PADDLE_ONLY_CPU
TEST
(
Projection
,
conv
)
{
testProjectionConv
(
1
);
testProjectionConv
(
3
);
}
#endif
TEST
(
Layer
,
BilinearInterpLayer
)
{
...
...
paddle/gserver/tests/test_NetworkCompare.cpp
浏览文件 @
7105962f
...
...
@@ -255,6 +255,16 @@ TEST(Compare, img_conv) {
compareNetwork
(
config_file_a
,
config_file_b
);
FLAGS_use_gpu
=
useGpu
;
}
// Test cudnn_conv and exconv give the same result
TEST
(
Compare
,
img_conv2
)
{
std
::
string
config_file_a
=
"./gserver/tests/img_conv_a.conf"
;
std
::
string
config_file_b
=
"./gserver/tests/img_conv_c.conf"
;
bool
useGpu
=
FLAGS_use_gpu
;
FLAGS_use_gpu
=
true
;
compareNetwork
(
config_file_a
,
config_file_b
);
FLAGS_use_gpu
=
useGpu
;
}
#endif
P_DEFINE_string
(
config_file_a
,
""
,
"config of one network to compare"
);
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
7105962f
...
...
@@ -698,7 +698,8 @@ class ConvProjection(Projection):
ci
=
self
.
proj_conf
.
conv_conf
.
channels
fh
=
self
.
proj_conf
.
conv_conf
.
filter_size
fw
=
self
.
proj_conf
.
conv_conf
.
filter_size_y
return
co
*
ci
*
fh
*
fw
gr
=
self
.
proj_conf
.
conv_conf
.
groups
return
co
*
ci
*
fh
*
fw
/
gr
def
calc_bias_size
(
self
):
return
self
.
proj_conf
.
num_filters
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
7105962f
...
...
@@ -129,6 +129,9 @@ class LayerType(object):
HSIGMOID
=
'hsigmoid'
CONV_LAYER
=
"conv"
CONVTRANS_LAYER
=
"convt"
EXCONV_LAYER
=
"exconv"
EXCONVTRANS_LAYER
=
"exconvt"
CUDNNCONV_LAYER
=
"cudnn_conv"
POOL_LAYER
=
"pool"
BATCH_NORM_LAYER
=
'batch_norm'
NORM_LAYER
=
'norm'
...
...
@@ -1762,7 +1765,8 @@ def img_conv_layer(input,
filter_size_y
=
None
,
stride_y
=
None
,
padding_y
=
None
,
trans
=
False
):
trans
=
False
,
layer_type
=
None
):
"""
Convolution layer for image. Paddle only support square input currently and
thus input image's width equals height.
...
...
@@ -1829,6 +1833,10 @@ def img_conv_layer(input,
:type layer_attr: ExtraLayerAttribute
:param trans: true if it is a convTransLayer, false if it is a convLayer
:type trans: bool
:param layer_type: specify the layer_type, default is None. If trans=True,
layer_type has to be "exconvt", otherwise layer_type
has to be either "exconv" or "cudnn_conv"
:type layer_type: String
:return: LayerOutput object.
:rtype: LayerOutput
"""
...
...
@@ -1864,8 +1872,15 @@ def img_conv_layer(input,
param_attr
.
attr
[
"initial_std"
]
=
init_w
param_attr
.
attr
[
"initial_strategy"
]
=
0
param_attr
.
attr
[
"initial_smart"
]
=
False
lt
=
LayerType
.
CONVTRANS_LAYER
if
trans
else
LayerType
.
CONV_LAYER
if
layer_type
:
if
trans
:
assert
layer_type
in
[
"exconvt"
]
else
:
assert
layer_type
in
[
"exconv"
,
"cudnn_conv"
]
lt
=
layer_type
else
:
lt
=
LayerType
.
CONVTRANS_LAYER
if
trans
else
LayerType
.
CONV_LAYER
l
=
Layer
(
name
=
name
,
...
...
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