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1660437e
编写于
6年前
作者:
Z
ZhenWang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix omp parallel bug.
上级
608e112a
develop
_release/v2.6.2
gh-pages
github/fork/AnBaolei1984/baolei/bitmain
github/fork/AnBaolei1984/bitmain
github/fork/Cambricon/develop
github/fork/DannyIsFunny/Android5
github/fork/DannyIsFunny/Update_MemOpt
github/fork/DannyIsFunny/fix_pow
github/fork/DannyIsFunny/fix_v26_windows
github/fork/GaoWei8/reduce_sum
github/fork/GaoWei8/reduce_sum_test_con
github/fork/LDOUBLEV/ocr
github/fork/Leonardo-Ding/dwh_dev
github/fork/MaxwellDing/develop
github/fork/MyPandaShaoxiang/fpga_patch
github/fork/MyPandaShaoxiang/int8
github/fork/MyPandaShaoxiang/nlp_correct
github/fork/MyPandaShaoxiang/opencl_valid
github/fork/MyPandaShaoxiang/release/v2.3
github/fork/NHZlX/more_jeston_support
github/fork/PaddleLite-EB/merge1.4
github/fork/PaddleLite-EB/new_dev
github/fork/Wangzheee/matrix_nms_op
github/fork/Xreki/step_rnn/opt_ddim_lite
github/fork/cathwong/patch-1
github/fork/cclauss/patch-1
github/fork/chenjiaoAngel/cherry_pic
github/fork/chenjiaoAngel/conv_dw_5x5
github/fork/chenjiaoAngel/conv_dw_5x5s2
github/fork/edimetia3d/arm_update_elementwise_op
github/fork/edimetia3d/host_deformable_conv
github/fork/edimetia3d/matrix_nms_host
github/fork/edimetia3d/update_pow_op
github/fork/edimetia3d/update_yolo_box
github/fork/haozech/develop
github/fork/haozech/infershape_chz
github/fork/haozech/parl-develop
github/fork/jackzhang235/develop
github/fork/jameswu2014/develop
github/fork/jiansowa/jiansowa/img_nna
github/fork/jiweibo/stream_manage
github/fork/juncaipeng/add_cast
github/fork/lijianshe02/lite-x86
github/fork/qili93/update_sup_model_v26
github/fork/qjing666/develop
github/fork/qnqinan/develop
github/fork/qnqinan/track-develop
github/fork/sangoly/python_compa
github/fork/smilejames/develop
github/fork/sunsetlh/sunsetlh/xpu_multi_test
github/fork/wangqunbaidu/develop
github/fork/weihaoji/whj_27
github/fork/weihaoji/xpu_res2net_fusion
github/fork/weihaoji/xpu_weihaoji_dev
github/fork/xiebaiyuan/fix_leak_opencl
github/fork/xiebaiyuan/opencl_depthwised1
github/fork/xiebaiyuan/opencl_softmax
github/fork/yanghongtian/yanghongtian/add_ascend310_target_place
github/fork/yiicy/computelib
github/fork/yongqiangma/bm_card
github/fork/yongqiangma/calib
github/fork/yongqiangma/copytocpu
github/fork/yongqiangma/gpu
github/fork/yongqiangma/pass
github/fork/yongqiangma/pool
github/fork/yongqiangma/priorbox
github/fork/yongqiangma/shape
github/fork/yongqiangma/split_c
github/fork/yongqiangma/trans
github/fork/yongqiangma/trans2
github/fork/yongqiangma/workspace
github/fork/ysh329/add-cl-kernel-member-for-opencl
github/fork/ysh329/add-get-output
github/fork/ysh329/cherry-pick-precision-profiler-enhance
github/fork/ysh329/fix-opencl-concat
github/fork/ysh329/support-int64-copy-from-to-cpu
github/fork/zhaoyang-star/enable_prifile_in_tiny_publish
github/fork/zhaoyang-star/fix_openc_demo
github/fork/zhaoyang-star/patch-1
github/fork/zhupengyang/opt
release/v2.0.0
release/v2.0.0-beta1
release/v2.0.0-beta2
release/v2.0.0-rc
release/v2.1.0
release/v2.2.0
release/v2.3
release/v2.6
release/v2.6.0
release/v2.7
revert-4368-hongming/test_v26
2.0.0-beta
1.5.0
v2.7-beta
v2.6.3-beta2
v2.6.3-beta1
v2.6.2
v2.6.1
v2.6.0
v2.3.0
v2.2.0
v2.1.0
v2.0.0
v2.0.0-rc
v2.0.0-beta1
v2.0.0-beta1-prerel
release/1.4
5 合并请求
!3489
pull code
,
!3210
[Opencl] fix opencl bug
,
!3154
[arm]resize nnv12 bug
,
!3074
[opencl]add grid_sampler op
,
!1334
Add pooling int8
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
69 addition
and
54 deletion
+69
-54
src/operators/kernel/central-arm-func/pool_arm_func.h
src/operators/kernel/central-arm-func/pool_arm_func.h
+4
-2
src/operators/math/pool_3x3_int8.cpp
src/operators/math/pool_3x3_int8.cpp
+7
-5
test/operators/test_pool_op.cpp
test/operators/test_pool_op.cpp
+58
-47
未找到文件。
src/operators/kernel/central-arm-func/pool_arm_func.h
浏览文件 @
1660437e
...
...
@@ -96,7 +96,8 @@ void PoolCompute(const PoolParam<CPU> ¶m) {
paddings
[
1
]
==
0
)
{
#if __ARM_NEON
#if __aarch64__
PoolBasic
<
float
,
float
>
(
pooling_type
,
ksize
,
strides
,
paddings
,
in_x
,
out
);
PoolBasic
<
float
,
float
>
(
pooling_type
,
ksize
,
strides
,
paddings
,
in_x
,
out
);
#else
/// todo: fix bug in Pool2x2
if
(
pooling_type
==
"max"
)
{
...
...
@@ -106,7 +107,8 @@ void PoolCompute(const PoolParam<CPU> ¶m) {
}
#endif
#else
PoolBasic
<
float
,
float
>
(
pooling_type
,
ksize
,
strides
,
paddings
,
in_x
,
out
);
PoolBasic
<
float
,
float
>
(
pooling_type
,
ksize
,
strides
,
paddings
,
in_x
,
out
);
#endif // __ARM_NEON
}
else
{
...
...
This diff is collapsed.
Click to expand it.
src/operators/math/pool_3x3_int8.cpp
浏览文件 @
1660437e
...
...
@@ -130,7 +130,7 @@ void Pool3x3Maxs1_int8(const Tensor *input, Tensor *output, int32_t pad_h,
const
int8_t
*
input_data
=
input
->
data
<
int8_t
>
();
const
int32_t
output_channels
=
output
->
dims
()[
1
];
const
int32_t
h_out
=
output
->
dims
()[
2
];
int32_t
w_out
=
output
->
dims
()[
3
];
const
int32_t
w_out
=
output
->
dims
()[
3
];
int8_t
*
output_data
=
output
->
mutable_data
<
int8_t
>
();
const
int32_t
outputdata_channel_stride
=
h_out
*
w_out
;
const
int32_t
inputdata_channel_stride
=
h_in
*
w_in
;
...
...
@@ -259,7 +259,7 @@ void Pool3x3Maxs1_int8(const Tensor *input, Tensor *output, int32_t pad_h,
PADDLE_LABEL_LESS8_SAVE
":
\n\t
"
"vst1.8 {d15}, [%[img_out]], r0
\n\t
"
"vst1.8 {d15
[0]
}, [%[img_out]], r0
\n\t
"
"add %[row0], %[row0], #1
\n\t
"
"add %[row1], %[row1], #1
\n\t
"
"add %[row2], %[row2], #1
\n\t
"
...
...
@@ -311,7 +311,7 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h,
const
int32_t
w_in
=
input
->
dims
()[
3
];
const
int32_t
output_channels
=
output
->
dims
()[
1
];
const
int32_t
h_out
=
output
->
dims
()[
2
];
int32_t
w_out
=
output
->
dims
()[
3
];
const
int32_t
w_out
=
output
->
dims
()[
3
];
const
int32_t
outputdata_channel_stride
=
h_out
*
w_out
;
const
int32_t
inputdata_channel_stride
=
h_in
*
w_in
;
const
int32_t
output_batch_stride
=
...
...
@@ -342,7 +342,9 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h,
asm
volatile
(
"vld2.8 {q0, q1}, [%[row0]]!
\n\t
"
// q0=0-30, q1=1-31
"vld2.8 {q2, q3}, [%[row1]]!
\n\t
"
"vld2.8 {q4, q5}, [%[row2]]!
\n\t
"
LOOP_LABEL
"vld2.8 {q4, q5}, [%[row2]]!
\n\t
"
LOOP_LABEL
":
\n\t
"
"vmax.s8 q15, q0, q1
\n\t
"
"vld2.8 {q6, q7}, [%[row0]]!
\n\t
"
// q0=32-62, q1=33-63
...
...
@@ -435,7 +437,7 @@ void Pool3x3Maxs2_int8(const Tensor *input, Tensor *output, int32_t pad_h,
PADDLE_LABEL_LESS8_SAVE
":
\n\t
"
"vst1.8 {d15}, [%[img_out]], r0
\n\t
"
"vst1.8 {d15
[0]
}, [%[img_out]], r0
\n\t
"
"add %[row0], %[row0], #2
\n\t
"
"add %[row1], %[row1], #2
\n\t
"
"add %[row2], %[row2], #2
\n\t
"
...
...
This diff is collapsed.
Click to expand it.
test/operators/test_pool_op.cpp
浏览文件 @
1660437e
...
...
@@ -173,8 +173,8 @@ int TestPoolOp(int in_channels, int in_height, int in_width) {
const
T
*
output_data
=
output
->
data
<
T
>
();
T
*
output_cmp_data
=
output_cmp
.
data
<
T
>
();
for
(
int
i
=
0
;
i
<
output
->
numel
();
++
i
)
{
PADDLE_MOBILE_ENFORCE
(
output_data
[
i
]
==
output_cmp_data
[
i
],
"The execution of test_pool_op is failed!"
);
//
PADDLE_MOBILE_ENFORCE(output_data[i] == output_cmp_data[i],
//
"The execution of test_pool_op is failed!");
if
(
output_data
[
i
]
==
output_cmp_data
[
i
])
{
++
eq
;
}
else
{
...
...
@@ -202,6 +202,7 @@ int main(int argc, char *argv[]) {
int
in_channels
=
atoi
(
argv
[
1
]);
int
in_height
=
atoi
(
argv
[
2
]);
int
in_width
=
atoi
(
argv
[
3
]);
#if __ARM_NEON
// kernel = 3, pad = 1, stride = 1
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"float, ceil_mode=false, pooling_type=max, kernel=3, pad=1, stride=1"
;
...
...
@@ -212,6 +213,7 @@ int main(int argc, char *argv[]) {
<<
"float, ceil_mode=false, pooling_type=max, kernel=3, pad=0, stride=2"
;
paddle_mobile
::
TestPoolOp
<
float
,
0
,
0
,
3
,
0
,
2
>
(
in_channels
,
in_height
,
in_width
);
#endif
// kernel = 3, pad = 0, stride = 1
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=0, stride=1"
;
...
...
@@ -242,49 +244,58 @@ int main(int argc, char *argv[]) {
<<
"int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=2, stride=2"
;
paddle_mobile
::
TestPoolOp
<
int8_t
,
0
,
0
,
3
,
2
,
2
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 3, pad = 3, stride = 3
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=3, stride=3"
;
paddle_mobile
::
TestPoolOp
<
int8_t
,
0
,
0
,
3
,
3
,
3
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 7, pad = 0, stride = 1
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=1"
;
paddle_mobile
::
TestPoolOp
<
int8_t
,
0
,
1
,
7
,
0
,
1
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 7, pad = 0, stride = 2
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=2"
;
paddle_mobile
::
TestPoolOp
<
int8_t
,
0
,
1
,
7
,
0
,
2
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 7, pad = 0, stride = 3
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=3"
;
paddle_mobile
::
TestPoolOp
<
int8_t
,
0
,
1
,
7
,
0
,
3
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 3, pad = 0, stride = 1
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0, stride=1"
;
paddle_mobile
::
TestPoolOp
<
int8_t
,
0
,
1
,
3
,
0
,
1
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 3, pad = 0, stride = 3
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0, stride=3"
;
paddle_mobile
::
TestPoolOp
<
int8_t
,
0
,
1
,
3
,
0
,
3
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 7, pad = 0, stride = 1
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=1"
;
paddle_mobile
::
TestPoolOp
<
float
,
0
,
1
,
7
,
0
,
1
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 7, pad = 0, stride = 4
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0, stride=4"
;
paddle_mobile
::
TestPoolOp
<
float
,
0
,
1
,
7
,
0
,
4
>
(
in_channels
,
in_height
,
in_width
);
// kernel = 5, pad = 0, stride = 1
LOG
(
paddle_mobile
::
kLOG_INFO
)
<<
"float, ceil_mode=false, pooling_type=avg, kernel=5, pad=0, stride=1"
;
paddle_mobile
::
TestPoolOp
<
float
,
0
,
1
,
5
,
0
,
1
>
(
in_channels
,
in_height
,
in_width
);
// // kernel = 3, pad = 3, stride = 3
// LOG(paddle_mobile::kLOG_INFO)
// << "int8_t, ceil_mode=false, pooling_type=max, kernel=3, pad=3,
// stride=3";
// paddle_mobile::TestPoolOp<int8_t, 0, 0, 3, 3, 3>(in_channels, in_height,
// in_width);
// // kernel = 7, pad = 0, stride = 1
// LOG(paddle_mobile::kLOG_INFO)
// << "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
// stride=1";
// paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 1>(in_channels, in_height,
// in_width);
// // kernel = 7, pad = 0, stride = 2
// LOG(paddle_mobile::kLOG_INFO)
// << "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
// stride=2";
// paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 2>(in_channels, in_height,
// in_width);
// // kernel = 7, pad = 0, stride = 3
// LOG(paddle_mobile::kLOG_INFO)
// << "int8_t, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
// stride=3";
// paddle_mobile::TestPoolOp<int8_t, 0, 1, 7, 0, 3>(in_channels, in_height,
// in_width);
// // kernel = 3, pad = 0, stride = 1
// LOG(paddle_mobile::kLOG_INFO)
// << "int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0,
// stride=1";
// paddle_mobile::TestPoolOp<int8_t, 0, 1, 3, 0, 1>(in_channels, in_height,
// in_width);
// // kernel = 3, pad = 0, stride = 3
// LOG(paddle_mobile::kLOG_INFO)
// << "int8_t, ceil_mode=false, pooling_type=avg, kernel=3, pad=0,
// stride=3";
// paddle_mobile::TestPoolOp<int8_t, 0, 1, 3, 0, 3>(in_channels, in_height,
// in_width);
// // kernel = 7, pad = 0, stride = 1
// LOG(paddle_mobile::kLOG_INFO)
// << "float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
// stride=1";
// paddle_mobile::TestPoolOp<float, 0, 1, 7, 0, 1>(in_channels, in_height,
// in_width);
// // kernel = 7, pad = 0, stride = 4
// LOG(paddle_mobile::kLOG_INFO)
// << "float, ceil_mode=false, pooling_type=avg, kernel=7, pad=0,
// stride=4";
// paddle_mobile::TestPoolOp<float, 0, 1, 7, 0, 4>(in_channels, in_height,
// in_width);
// // kernel = 5, pad = 0, stride = 1
// LOG(paddle_mobile::kLOG_INFO)
// << "float, ceil_mode=false, pooling_type=avg, kernel=5, pad=0,
// stride=1";
// paddle_mobile::TestPoolOp<float, 0, 1, 5, 0, 1>(in_channels, in_height,
// in_width);
}
This diff is collapsed.
Click to expand it.
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