Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
PaddleDetection
提交
266e625d
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
大约 1 年 前同步成功
通知
695
Star
11112
Fork
2696
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
184
列表
看板
标记
里程碑
合并请求
40
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
PaddleDetection
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
184
Issue
184
列表
看板
标记
里程碑
合并请求
40
合并请求
40
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
未验证
提交
266e625d
编写于
1月 21, 2019
作者:
T
tensor-tang
提交者:
GitHub
1月 21, 2019
浏览文件
操作
浏览文件
下载
差异文件
Merge pull request #15399 from tensor-tang/refine/seqpool/fc
fix cpu jitkernel test and refine benchmark test
上级
885c4e57
316e44b1
变更
2
显示空白变更内容
内联
并排
Showing
2 changed file
with
118 addition
and
43 deletion
+118
-43
paddle/fluid/operators/jit/benchmark.cc
paddle/fluid/operators/jit/benchmark.cc
+98
-33
paddle/fluid/operators/jit/test.cc
paddle/fluid/operators/jit/test.cc
+20
-10
未找到文件。
paddle/fluid/operators/jit/benchmark.cc
浏览文件 @
266e625d
...
...
@@ -22,10 +22,54 @@
#include "paddle/fluid/platform/device_tracer.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/platform/variant.h" // for UNUSED
DEFINE_int32
(
burning
,
10
,
"Burning times."
);
DEFINE_int32
(
repeat
,
3000
,
"Repeat times."
);
DEFINE_int32
(
max_size
,
1000
,
"The Max size would be tested."
);
DEFINE_string
(
filter
,
""
,
"The Benchmark name would be run."
);
class
BenchJITKernel
{
public:
BenchJITKernel
()
=
default
;
virtual
~
BenchJITKernel
()
=
default
;
virtual
void
Run
()
=
0
;
virtual
const
char
*
Name
()
=
0
;
virtual
const
char
*
Dtype
()
=
0
;
virtual
const
char
*
Place
()
=
0
;
};
static
std
::
vector
<
BenchJITKernel
*>
g_all_benchmarks
;
BenchJITKernel
*
InsertBenchmark
(
BenchJITKernel
*
b
)
{
g_all_benchmarks
.
push_back
(
b
);
return
b
;
}
#define BENCH_JITKERNEL(name, dtype, place) \
class BenchJITKernel_##name##_##dtype##_##place##_ : public BenchJITKernel { \
public: \
const char* Name() override { return #name; } \
const char* Dtype() override { return #dtype; } \
const char* Place() override { return #place; } \
void Run() override; \
}; \
static auto inserted_##name##_##dtype##_##place##_ UNUSED = \
InsertBenchmark(new BenchJITKernel_##name##_##dtype##_##place##_()); \
void BenchJITKernel_##name##_##dtype##_##place##_::Run()
#define BENCH_FP32_CPU(name) BENCH_JITKERNEL(name, FP32, CPU)
void
RUN_ALL_BENCHMARK
()
{
for
(
auto
p
:
g_all_benchmarks
)
{
if
(
!
FLAGS_filter
.
empty
()
&&
FLAGS_filter
!=
p
->
Name
())
{
continue
;
}
LOG
(
INFO
)
<<
"Benchmark "
<<
p
->
Name
()
<<
"."
<<
p
->
Dtype
()
<<
"."
<<
p
->
Place
();
p
->
Run
();
}
}
template
<
typename
T
>
void
RandomVec
(
const
int
n
,
T
*
a
,
const
T
lower
=
static_cast
<
T
>
(
-
20.
f
),
...
...
@@ -228,49 +272,70 @@ void BenchMatMulKernel() {
}
}
using
T
=
float
;
using
PlaceType
=
paddle
::
platform
::
CPUPlace
;
// xyzn
BENCH_FP32_CPU
(
kVMul
)
{
BenchXYZNKernel
<
jit
::
kVMul
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVAdd
)
{
BenchXYZNKernel
<
jit
::
kVAdd
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVAddRelu
)
{
BenchXYZNKernel
<
jit
::
kVAddRelu
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVSub
)
{
BenchXYZNKernel
<
jit
::
kVSub
,
T
,
PlaceType
>
();
}
// axyn
BENCH_FP32_CPU
(
kVScal
)
{
BenchAXYNKernel
<
jit
::
kVScal
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVAddBias
)
{
BenchAXYNKernel
<
jit
::
kVAddBias
,
T
,
PlaceType
>
();
}
// xyn
BENCH_FP32_CPU
(
kVRelu
)
{
BenchXYNKernel
<
jit
::
kVRelu
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVIdentity
)
{
BenchXYNKernel
<
jit
::
kVIdentity
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVSquare
)
{
BenchXYNKernel
<
jit
::
kVSquare
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVExp
)
{
BenchXYNKernel
<
jit
::
kVExp
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVSigmoid
)
{
BenchXYNKernel
<
jit
::
kVSigmoid
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kVTanh
)
{
BenchXYNKernel
<
jit
::
kVTanh
,
T
,
PlaceType
>
();
}
// lstm and peephole
BENCH_FP32_CPU
(
kLSTMCtHt
)
{
BenchLSTMKernel
<
jit
::
kLSTMCtHt
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kLSTMC1H1
)
{
BenchLSTMKernel
<
jit
::
kLSTMC1H1
,
T
,
PlaceType
>
();
}
// gru functions
BENCH_FP32_CPU
(
kGRUH1
)
{
BenchGRUKernel
<
jit
::
kGRUH1
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kGRUHtPart1
)
{
BenchGRUKernel
<
jit
::
kGRUHtPart1
,
T
,
PlaceType
>
();
}
BENCH_FP32_CPU
(
kGRUHtPart2
)
{
BenchGRUKernel
<
jit
::
kGRUHtPart2
,
T
,
PlaceType
>
();
}
// seq pool function
BENCH_FP32_CPU
(
kSeqPool
)
{
BenchSeqPoolKernel
<
jit
::
kSeqPool
,
T
,
PlaceType
>
();
}
// matmul
BENCH_FP32_CPU
(
kMatMul
)
{
BenchMatMulKernel
<
jit
::
kMatMul
,
T
,
PlaceType
>
();
}
// Benchmark all jit kernels including jitcode, mkl and refer.
// To use this tool, run command: ./benchmark [options...]
// Options:
// --burning: the burning time before count
// --repeat: the repeat times
// --max_size: the max size would be tested
// --filter: the bench name would be run
int
main
(
int
argc
,
char
*
argv
[])
{
gflags
::
ParseCommandLineFlags
(
&
argc
,
&
argv
,
true
);
google
::
InitGoogleLogging
(
argv
[
0
]);
LOG
(
INFO
)
<<
"Burning "
<<
FLAGS_burning
<<
" times, Repeat "
<<
FLAGS_repeat
<<
" times."
;
using
T
=
float
;
using
PlaceType
=
paddle
::
platform
::
CPUPlace
;
// xyzn
BenchXYZNKernel
<
jit
::
kVMul
,
T
,
PlaceType
>
();
BenchXYZNKernel
<
jit
::
kVAdd
,
T
,
PlaceType
>
();
BenchXYZNKernel
<
jit
::
kVAddRelu
,
T
,
PlaceType
>
();
BenchXYZNKernel
<
jit
::
kVSub
,
T
,
PlaceType
>
();
// axyn
BenchAXYNKernel
<
jit
::
kVScal
,
T
,
PlaceType
>
();
BenchAXYNKernel
<
jit
::
kVAddBias
,
T
,
PlaceType
>
();
// xyn
BenchXYNKernel
<
jit
::
kVRelu
,
T
,
PlaceType
>
();
BenchXYNKernel
<
jit
::
kVIdentity
,
T
,
PlaceType
>
();
BenchXYNKernel
<
jit
::
kVSquare
,
T
,
PlaceType
>
();
BenchXYNKernel
<
jit
::
kVExp
,
T
,
PlaceType
>
();
BenchXYNKernel
<
jit
::
kVSigmoid
,
T
,
PlaceType
>
();
BenchXYNKernel
<
jit
::
kVTanh
,
T
,
PlaceType
>
();
// lstm and peephole
BenchLSTMKernel
<
jit
::
kLSTMCtHt
,
T
,
PlaceType
>
();
BenchLSTMKernel
<
jit
::
kLSTMC1H1
,
T
,
PlaceType
>
();
// gru functions
BenchGRUKernel
<
jit
::
kGRUH1
,
T
,
PlaceType
>
();
BenchGRUKernel
<
jit
::
kGRUHtPart1
,
T
,
PlaceType
>
();
BenchGRUKernel
<
jit
::
kGRUHtPart2
,
T
,
PlaceType
>
();
// seq pool function
BenchSeqPoolKernel
<
jit
::
kSeqPool
,
T
,
PlaceType
>
();
// matmul
BenchMatMulKernel
<
jit
::
kMatMul
,
T
,
PlaceType
>
();
RUN_ALL_BENCHMARK
();
}
paddle/fluid/operators/jit/test.cc
浏览文件 @
266e625d
...
...
@@ -22,6 +22,8 @@
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/place.h"
static
double
acc
=
1e-5
;
template
<
typename
T
>
void
RandomVec
(
const
int
n
,
T
*
a
,
const
T
lower
=
static_cast
<
T
>
(
-
20.
f
),
const
T
upper
=
static_cast
<
T
>
(
20.
f
))
{
...
...
@@ -37,7 +39,7 @@ template <typename T>
void
ExpectEQ
(
const
T
*
target
,
const
T
*
refer
,
int
n
)
{
if
(
std
::
is_floating_point
<
T
>::
value
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
EXPECT_NEAR
(
target
[
i
],
refer
[
i
],
1e-5
);
EXPECT_NEAR
(
target
[
i
],
refer
[
i
],
acc
);
}
}
else
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
...
...
@@ -62,7 +64,9 @@ namespace jit = paddle::operators::jit;
template
<
typename
KernelTuples
,
typename
...
Args
>
struct
TestFuncWithRefer
{
void
operator
()(
const
typename
KernelTuples
::
func_type
tgt
,
Args
...
args
)
{}
void
operator
()(
const
typename
KernelTuples
::
func_type
tgt
,
Args
...
args
)
{
LOG
(
FATAL
)
<<
"Should specify this function."
;
}
};
template
<
typename
T
>
...
...
@@ -140,7 +144,8 @@ struct TestFuncWithRefer<jit::XYNTuples<T>, std::vector<T>, std::vector<T>> {
template
<
typename
T
>
struct
TestFuncWithRefer
<
jit
::
LSTMTuples
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>>
{
std
::
vector
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>
,
typename
jit
::
LSTMTuples
<
T
>::
attr_type
>
{
void
operator
()(
const
typename
jit
::
LSTMTuples
<
T
>::
func_type
tgt
,
const
std
::
vector
<
T
>&
xsrc
,
const
std
::
vector
<
T
>&
wp
,
const
std
::
vector
<
T
>&
ct_1
,
const
std
::
vector
<
T
>&
ct_ref
,
...
...
@@ -185,7 +190,8 @@ struct TestFuncWithRefer<jit::LSTMTuples<T>, std::vector<T>, std::vector<T>,
template
<
typename
T
>
struct
TestFuncWithRefer
<
jit
::
GRUTuples
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>>
{
std
::
vector
<
T
>
,
typename
jit
::
GRUTuples
<
T
>::
attr_type
>
{
void
operator
()(
const
typename
jit
::
GRUTuples
<
T
>::
func_type
tgt
,
const
std
::
vector
<
T
>&
xsrc
,
const
std
::
vector
<
T
>&
ht_1
,
const
std
::
vector
<
T
>&
ht_ref
,
...
...
@@ -212,8 +218,8 @@ struct TestFuncWithRefer<jit::GRUTuples<T>, std::vector<T>, std::vector<T>,
};
template
<
typename
T
>
struct
TestFuncWithRefer
<
jit
::
SeqPoolTuples
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>
>
{
struct
TestFuncWithRefer
<
jit
::
SeqPoolTuples
<
T
>
,
std
::
vector
<
T
>
,
std
::
vector
<
T
>
,
typename
jit
::
SeqPoolTuples
<
T
>::
attr_type
>
{
void
operator
()(
const
typename
jit
::
SeqPoolTuples
<
T
>::
func_type
tgt
,
const
std
::
vector
<
T
>&
x
,
const
std
::
vector
<
T
>&
yref
,
const
typename
jit
::
SeqPoolTuples
<
T
>::
attr_type
&
attr
)
{
...
...
@@ -385,8 +391,8 @@ void TestLSTMKernel() {
std
::
vector
<
T
>
xsrc
(
4
*
d
),
wp
(
3
*
d
),
ct_1
(
d
);
std
::
vector
<
T
>
ct_ref
(
d
),
ht_ref
(
d
),
checked
(
2
*
d
);
RandomVec
<
T
>
(
4
*
d
,
xsrc
.
data
(),
-
2.
f
,
2.
f
);
RandomVec
<
T
>
(
3
*
d
,
wp
.
data
(),
-
2.
f
,
2
.
f
);
RandomVec
<
T
>
(
d
,
ct_1
.
data
(),
-
2.
f
,
2
.
f
);
RandomVec
<
T
>
(
3
*
d
,
wp
.
data
(),
-
1.
f
,
1
.
f
);
RandomVec
<
T
>
(
d
,
ct_1
.
data
(),
-
1.
f
,
1
.
f
);
// x could be changed after compute, so copy to save src
std
::
vector
<
T
>
x
(
xsrc
.
size
());
std
::
copy
(
xsrc
.
begin
(),
xsrc
.
end
(),
x
.
begin
());
...
...
@@ -481,14 +487,17 @@ void TestSeqPoolKernel() {
template
<
paddle
::
operators
::
jit
::
KernelType
KT
,
typename
T
,
typename
PlaceType
>
void
TestMatMulKernel
()
{
VLOG
(
10
)
<<
"===== Test JITKernel "
<<
jit
::
to_string
(
KT
);
auto
last_acc
=
acc
;
// TODO(intel): this should be acc issue of MKL
acc
=
1e-3
;
for
(
int
m
:
{
1
,
2
,
3
,
4
})
{
for
(
int
n
:
{
1
,
2
,
3
,
4
})
{
for
(
int
k
:
TestSizes
())
{
auto
ref
=
jit
::
GetRefer
<
KT
,
jit
::
MatMulTuples
<
T
>>
();
EXPECT_TRUE
(
ref
!=
nullptr
);
std
::
vector
<
T
>
a
(
m
*
k
),
b
(
k
*
n
),
c
(
m
*
n
);
RandomVec
<
T
>
(
m
*
k
,
a
.
data
(),
-
0.2
f
,
0.2
f
);
RandomVec
<
T
>
(
k
*
n
,
b
.
data
(),
-
0.2
f
,
0.2
f
);
RandomVec
<
T
>
(
m
*
k
,
a
.
data
(),
-
2.
f
,
2.
f
);
RandomVec
<
T
>
(
k
*
n
,
b
.
data
(),
-
2.
f
,
2.
f
);
const
T
*
a_data
=
a
.
data
();
const
T
*
b_data
=
b
.
data
();
T
*
c_data
=
c
.
data
();
...
...
@@ -498,6 +507,7 @@ void TestMatMulKernel() {
}
}
}
acc
=
last_acc
;
}
template
<
paddle
::
operators
::
jit
::
KernelType
KT
,
typename
T
,
typename
PlaceType
>
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录