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a785496b
编写于
12月 22, 2017
作者:
T
tensor-tang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix logical error
上级
86b8bdc0
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
14 addition
and
26 deletion
+14
-26
benchmark/paddle/image/alexnet.py
benchmark/paddle/image/alexnet.py
+10
-22
benchmark/paddle/image/run_mkl_infer.sh
benchmark/paddle/image/run_mkl_infer.sh
+1
-1
benchmark/paddle/image/run_mkl_train.sh
benchmark/paddle/image/run_mkl_train.sh
+1
-1
benchmark/paddle/image/run_openblas_infer.sh
benchmark/paddle/image/run_openblas_infer.sh
+1
-1
benchmark/paddle/image/run_openblas_train.sh
benchmark/paddle/image/run_openblas_train.sh
+1
-1
未找到文件。
benchmark/paddle/image/alexnet.py
浏览文件 @
a785496b
...
...
@@ -6,7 +6,7 @@ height = 227
width
=
227
num_class
=
1000
batch_size
=
get_config_arg
(
'batch_size'
,
int
,
128
)
use_mkldnn
=
get_config_arg
(
'use_mkldnn'
,
bool
,
False
)
gp
=
get_config_arg
(
'layer_num'
,
int
,
1
)
is_infer
=
get_config_arg
(
"is_infer"
,
bool
,
False
)
num_samples
=
get_config_arg
(
'num_samples'
,
int
,
2560
)
...
...
@@ -41,12 +41,7 @@ net = img_pool_layer(input=net, pool_size=3, stride=2)
# conv2
net
=
img_conv_layer
(
input
=
net
,
filter_size
=
5
,
num_filters
=
256
,
stride
=
1
,
padding
=
2
,
groups
=
2
if
use_mkldnn
else
1
)
input
=
net
,
filter_size
=
5
,
num_filters
=
256
,
stride
=
1
,
padding
=
2
,
groups
=
gp
)
net
=
img_cmrnorm_layer
(
input
=
net
,
size
=
5
,
scale
=
0.0001
,
power
=
0.75
)
net
=
img_pool_layer
(
input
=
net
,
pool_size
=
3
,
stride
=
2
)
...
...
@@ -55,21 +50,11 @@ net = img_conv_layer(
input
=
net
,
filter_size
=
3
,
num_filters
=
384
,
stride
=
1
,
padding
=
1
)
# conv4
net
=
img_conv_layer
(
input
=
net
,
filter_size
=
3
,
num_filters
=
384
,
stride
=
1
,
padding
=
1
,
groups
=
2
if
use_mkldnn
else
1
)
input
=
net
,
filter_size
=
3
,
num_filters
=
384
,
stride
=
1
,
padding
=
1
,
groups
=
gp
)
# conv5
net
=
img_conv_layer
(
input
=
net
,
filter_size
=
3
,
num_filters
=
256
,
stride
=
1
,
padding
=
1
,
groups
=
2
if
use_mkldnn
else
1
)
input
=
net
,
filter_size
=
3
,
num_filters
=
256
,
stride
=
1
,
padding
=
1
,
groups
=
gp
)
net
=
img_pool_layer
(
input
=
net
,
pool_size
=
3
,
stride
=
2
)
net
=
fc_layer
(
...
...
@@ -84,6 +69,9 @@ net = fc_layer(
layer_attr
=
ExtraAttr
(
drop_rate
=
0.5
))
net
=
fc_layer
(
input
=
net
,
size
=
1000
,
act
=
SoftmaxActivation
())
lab
=
data_layer
(
'label'
,
num_class
)
loss
=
cross_entropy
(
input
=
net
,
label
=
lab
)
outputs
(
loss
)
if
is_infer
:
outputs
(
net
)
else
:
lab
=
data_layer
(
'label'
,
num_class
)
loss
=
cross_entropy
(
input
=
net
,
label
=
lab
)
outputs
(
loss
)
benchmark/paddle/image/run_mkl_infer.sh
浏览文件 @
a785496b
...
...
@@ -79,7 +79,7 @@ fi
# inference benchmark
for
use_mkldnn
in
True False
;
do
for
batchsize
in
1 2 4 8 16
;
do
infer alexnet
group
2
$batchsize
$use_mkldnn
infer alexnet 2
$batchsize
$use_mkldnn
infer googlenet v1
$batchsize
$use_mkldnn
infer resnet 50
$batchsize
$use_mkldnn
infer vgg 19
$batchsize
$use_mkldnn
...
...
benchmark/paddle/image/run_mkl_train.sh
浏览文件 @
a785496b
...
...
@@ -47,6 +47,6 @@ for use_mkldnn in True False; do
train vgg 19
$batchsize
$use_mkldnn
train resnet 50
$batchsize
$use_mkldnn
train googlenet v1
$batchsize
$use_mkldnn
train alexnet
group
2
$batchsize
$use_mkldnn
train alexnet 2
$batchsize
$use_mkldnn
done
done
benchmark/paddle/image/run_openblas_infer.sh
浏览文件 @
a785496b
...
...
@@ -56,7 +56,7 @@ fi
# inference benchmark
for
batchsize
in
1 2 4 8 16
;
do
infer alexnet
group
2
$batchsize
$use_mkldnn
infer alexnet 2
$batchsize
$use_mkldnn
infer googlenet v1
$batchsize
infer resnet 50
$batchsize
infer vgg 19
$batchsize
...
...
benchmark/paddle/image/run_openblas_train.sh
浏览文件 @
a785496b
...
...
@@ -36,5 +36,5 @@ for batchsize in 64 128 256; do
train vgg 19
$batchsize
train resnet 50
$batchsize
train googlenet v1
$batchsize
train alexnet
group
2
$batchsize
$use_mkldnn
train alexnet 2
$batchsize
$use_mkldnn
done
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