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23785584
编写于
10月 20, 2017
作者:
T
Tao Luo
提交者:
GitHub
10月 20, 2017
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差异文件
Merge pull request #4966 from tensor-tang/develop
add mkldnn branch tests for pool and fc
上级
9a5562aa
5b5cb078
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
119 addition
and
1 deletion
+119
-1
paddle/gserver/tests/mkldnn_branches_fc.conf
paddle/gserver/tests/mkldnn_branches_fc.conf
+58
-0
paddle/gserver/tests/mkldnn_branches_pool.conf
paddle/gserver/tests/mkldnn_branches_pool.conf
+60
-0
paddle/gserver/tests/test_MKLDNN.cpp
paddle/gserver/tests/test_MKLDNN.cpp
+1
-1
未找到文件。
paddle/gserver/tests/mkldnn_branches_fc.conf
0 → 100644
浏览文件 @
23785584
# Copyright (c) 2017 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.
from
paddle
.
trainer_config_helpers
import
*
settings
(
batch_size
=
16
)
channels
=
get_config_arg
(
"channels"
,
int
,
2
)
def
two_fc
(
input
,
group_name
):
out1
=
fc_layer
(
input
=
input
,
name
=
group_name
+
'_fc1'
,
size
=
channels
,
bias_attr
=
False
,
act
=
LinearActivation
())
out2
=
fc_layer
(
input
=
input
,
name
=
group_name
+
'_fc2'
,
size
=
channels
,
bias_attr
=
False
,
act
=
LinearActivation
())
return
out1
,
out2
data
=
data_layer
(
name
=
"input"
,
size
=
channels
*
16
*
16
)
conv
=
img_conv_layer
(
input
=
data
,
num_channels
=
channels
,
filter_size
=
3
,
num_filters
=
channels
,
padding
=
1
,
shared_biases
=
True
,
act
=
LinearActivation
())
pool
=
img_pool_layer
(
input
=
conv
,
pool_size
=
3
,
stride
=
2
,
padding
=
1
,
pool_type
=
AvgPooling
())
a1
,
a2
=
two_fc
(
input
=
pool
,
group_name
=
'a'
)
concat
=
concat_layer
(
input
=[
a1
,
a2
])
b1
,
b2
=
two_fc
(
input
=
pool
,
group_name
=
'b'
)
addto
=
addto_layer
(
input
=[
b1
,
b2
])
outputs
([
concat
,
addto
])
paddle/gserver/tests/mkldnn_branches_pool.conf
0 → 100644
浏览文件 @
23785584
# Copyright (c) 2017 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.
from
paddle
.
trainer_config_helpers
import
*
settings
(
batch_size
=
16
)
channels
=
get_config_arg
(
"channels"
,
int
,
2
)
def
two_pool
(
input
,
group_name
):
out1
=
img_pool_layer
(
input
=
input
,
name
=
group_name
+
'_pool1'
,
pool_size
=
3
,
stride
=
2
,
padding
=
0
,
pool_type
=
MaxPooling
())
out2
=
img_pool_layer
(
input
=
input
,
name
=
group_name
+
'_pool2'
,
pool_size
=
5
,
stride
=
2
,
padding
=
1
,
pool_type
=
MaxPooling
())
return
out1
,
out2
data
=
data_layer
(
name
=
"input"
,
size
=
channels
*
16
*
16
)
conv
=
img_conv_layer
(
input
=
data
,
num_channels
=
channels
,
filter_size
=
3
,
num_filters
=
channels
,
padding
=
1
,
shared_biases
=
True
,
act
=
LinearActivation
())
pool
=
img_pool_layer
(
input
=
conv
,
pool_size
=
3
,
stride
=
1
,
padding
=
1
,
pool_type
=
AvgPooling
())
a1
,
a2
=
two_pool
(
input
=
pool
,
group_name
=
'a'
)
concat
=
concat_layer
(
input
=[
a1
,
a2
])
b1
,
b2
=
two_pool
(
input
=
pool
,
group_name
=
'b'
)
addto
=
addto_layer
(
input
=[
b1
,
b2
])
outputs
([
concat
,
addto
])
paddle/gserver/tests/test_MKLDNN.cpp
浏览文件 @
23785584
...
...
@@ -250,7 +250,7 @@ TEST(MKLDNNActivation, Activations) {
DECLARE_string
(
config_args
);
TEST
(
MKLDNNLayer
,
branches
)
{
std
::
vector
<
std
::
string
>
cases
=
{
"conv"
};
std
::
vector
<
std
::
string
>
cases
=
{
"conv"
,
"pool"
,
"fc"
};
for
(
auto
name
:
cases
)
{
std
::
string
config
=
"./gserver/tests/mkldnn_branches_"
+
name
+
".conf"
;
for
(
auto
channels
:
{
2
,
32
})
{
...
...
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