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417d031f
编写于
12月 12, 2018
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
add refer vadd, vaddrelu, vsub and tests and benchmark
上级
f3250097
变更
10
显示空白变更内容
内联
并排
Showing
10 changed file
with
186 addition
and
93 deletion
+186
-93
paddle/fluid/operators/jit/README.md
paddle/fluid/operators/jit/README.md
+3
-3
paddle/fluid/operators/jit/benchmark.cc
paddle/fluid/operators/jit/benchmark.cc
+35
-31
paddle/fluid/operators/jit/helper.cc
paddle/fluid/operators/jit/helper.cc
+43
-0
paddle/fluid/operators/jit/helper.h
paddle/fluid/operators/jit/helper.h
+2
-0
paddle/fluid/operators/jit/kernel_base.h
paddle/fluid/operators/jit/kernel_base.h
+2
-2
paddle/fluid/operators/jit/more/mkl/mkl.h
paddle/fluid/operators/jit/more/mkl/mkl.h
+1
-1
paddle/fluid/operators/jit/refer/refer.cc
paddle/fluid/operators/jit/refer/refer.cc
+10
-2
paddle/fluid/operators/jit/refer/refer.h
paddle/fluid/operators/jit/refer/refer.h
+43
-4
paddle/fluid/operators/jit/test.cc
paddle/fluid/operators/jit/test.cc
+47
-20
paddle/fluid/operators/math/jit_kernel_refer.h
paddle/fluid/operators/math/jit_kernel_refer.h
+0
-30
未找到文件。
paddle/fluid/operators/jit/README.md
浏览文件 @
417d031f
...
...
@@ -41,6 +41,6 @@ PaddlePaddle/Paddle/paddle/fluid/
-
性能测试
# 如何添加新的算子
TBD
## Use me
Add USE_JIT_KERNEL(yourname) to CMakefile.
-
在
`KernelType`
中添加
`your_key`
-
实现Reference 的逻辑,每个jitkernel的Reference 实现是必须的。不要依赖任何第三方库。并在
`refer/CmakeLists.txt`
中
`USE_JITKERNEL_REFER(your_key)`
paddle/fluid/operators/jit/benchmark.cc
浏览文件 @
417d031f
...
...
@@ -52,9 +52,10 @@ std::vector<int> TestSizes() {
}
// return this function avg time
template
<
typename
T
,
typename
Func
>
double
BenchTartgetFunc
(
const
Func
tgt
,
const
std
::
vector
<
T
>&
x
,
const
std
::
vector
<
T
>&
y
,
std
::
vector
<
T
>&
z
)
{
// NOLINT
template
<
typename
T
,
typename
KernelTuples
>
double
BenchTartgetFunc
(
const
typename
KernelTuples
::
func_type
tgt
,
const
std
::
vector
<
T
>&
x
,
const
std
::
vector
<
T
>&
y
,
std
::
vector
<
T
>&
z
)
{
// NOLINT
const
T
*
x_data
=
x
.
data
();
const
T
*
y_data
=
y
.
data
();
const
int
d
=
z
.
size
();
...
...
@@ -71,40 +72,25 @@ double BenchTartgetFunc(const Func tgt, const std::vector<T>& x,
return
(
end
-
start
)
/
FLAGS_repeat
;
}
// 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
int
main
(
int
argc
,
char
*
argv
[])
{
gflags
::
ParseCommandLineFlags
(
&
argc
,
&
argv
,
true
);
google
::
InitGoogleLogging
(
argv
[
0
]);
using
T
=
float
;
using
PlaceType
=
paddle
::
platform
::
CPUPlace
;
template
<
paddle
::
operators
::
jit
::
KernelType
KT
,
typename
T
,
typename
PlaceType
>
void
BenchXYZNKernel
()
{
namespace
jit
=
paddle
::
operators
::
jit
;
const
auto
KT
=
jit
::
vmul
;
LOG
(
INFO
)
<<
"Burning "
<<
FLAGS_burning
<<
" times, Repeat "
<<
FLAGS_repeat
<<
" times."
;
for
(
int
d
:
TestSizes
())
{
// for (kernels type) { // TODO(TJ): more jit::KernelType
std
::
vector
<
std
::
pair
<
std
::
string
,
double
>>
infos
;
std
::
vector
<
T
>
x
(
d
),
y
(
d
),
z
(
d
);
RandomVec
<
T
>
(
d
,
x
.
data
());
RandomVec
<
T
>
(
d
,
y
.
data
());
// refer
auto
refer
=
jit
::
GetRefer
<
KT
,
jit
::
VMul
Tuples
<
T
>>
();
auto
refer
=
jit
::
GetRefer
<
KT
,
jit
::
XYZN
Tuples
<
T
>>
();
if
(
refer
)
{
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
VMulTuples
<
T
>::
func_type
>
(
refer
,
x
,
y
,
z
);
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
XYZNTuples
<
T
>>
(
refer
,
x
,
y
,
z
);
infos
.
push_back
(
std
::
make_pair
(
"Refer"
,
res
));
}
// test jitcode
auto
jitcode
=
jit
::
GetJitCode
<
KT
,
jit
::
VMul
Tuples
<
T
>
,
PlaceType
>
(
d
);
auto
jitcode
=
jit
::
GetJitCode
<
KT
,
jit
::
XYZN
Tuples
<
T
>
,
PlaceType
>
(
d
);
if
(
jitcode
)
{
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
VMulTuples
<
T
>::
func_type
>
(
jitcode
,
x
,
y
,
z
);
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
XYZNTuples
<
T
>>
(
jitcode
,
x
,
y
,
z
);
infos
.
push_back
(
std
::
make_pair
(
"JitCode"
,
res
));
}
...
...
@@ -115,32 +101,50 @@ int main(int argc, char* argv[]) {
if
(
iter
!=
pool
.
end
())
{
auto
&
impls
=
iter
->
second
;
for
(
auto
&
impl
:
impls
)
{
auto
i
=
dynamic_cast
<
const
jit
::
KernelImpl
<
jit
::
VMul
Tuples
<
T
>>*>
(
auto
i
=
dynamic_cast
<
const
jit
::
KernelImpl
<
jit
::
XYZN
Tuples
<
T
>>*>
(
impl
.
get
());
if
(
i
&&
i
->
UseMe
(
d
))
{
auto
more
=
i
->
GetFunc
();
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
VMulTuples
<
T
>::
func_type
>
(
more
,
x
,
y
,
z
);
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
XYZNTuples
<
T
>>
(
more
,
x
,
y
,
z
);
infos
.
push_back
(
std
::
make_pair
(
"More"
,
res
));
}
}
}
// Test result from Get function
auto
tgt
=
jit
::
Get
<
KT
,
jit
::
VMul
Tuples
<
T
>
,
PlaceType
>
(
d
);
auto
tgt
=
jit
::
Get
<
KT
,
jit
::
XYZN
Tuples
<
T
>
,
PlaceType
>
(
d
);
if
(
!
tgt
)
{
LOG
(
ERROR
)
<<
"Target can not be empty!"
;
}
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
VMulTuples
<
T
>::
func_type
>
(
tgt
,
x
,
y
,
z
);
auto
res
=
BenchTartgetFunc
<
T
,
jit
::
XYZNTuples
<
T
>
>
(
tgt
,
x
,
y
,
z
);
infos
.
push_back
(
std
::
make_pair
(
"Target"
,
res
));
// print
std
::
ostringstream
loginfos
;
loginfos
<<
"Kernel Type: "
<<
KT
<<
", size "
<<
d
<<
": "
;
loginfos
<<
"Kernel Type: "
<<
jit
::
to_string
(
KT
)
<<
", size "
<<
d
<<
": "
;
for
(
auto
pair
:
infos
)
{
loginfos
<<
pair
.
first
<<
" takes "
<<
pair
.
second
<<
" us; "
;
}
LOG
(
INFO
)
<<
loginfos
.
str
();
// }
}
}
// 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
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
;
namespace
jit
=
paddle
::
operators
::
jit
;
BenchXYZNKernel
<
jit
::
vmul
,
T
,
PlaceType
>
();
BenchXYZNKernel
<
jit
::
vadd
,
T
,
PlaceType
>
();
BenchXYZNKernel
<
jit
::
vaddrelu
,
T
,
PlaceType
>
();
BenchXYZNKernel
<
jit
::
vsub
,
T
,
PlaceType
>
();
}
paddle/fluid/operators/jit/helper.cc
0 → 100644
浏览文件 @
417d031f
/* Copyright (c) 2018 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. */
#include "paddle/fluid/operators/jit/helper.h"
namespace
paddle
{
namespace
operators
{
namespace
jit
{
const
char
*
to_string
(
KernelType
kt
)
{
switch
(
kt
)
{
case
vmul
:
return
"vmul"
;
case
vadd
:
return
"vadd"
;
case
vaddrelu
:
return
"vaddrelu"
;
case
vsub
:
return
"vsub"
;
case
vscal
:
return
"vscal"
;
case
vexp
:
return
"vexp"
;
default:
return
"NOT JITKernel"
;
}
return
nullptr
;
}
}
// namespace jit
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/jit/helper.h
浏览文件 @
417d031f
...
...
@@ -112,6 +112,8 @@ typename KernelTuples::func_type Get(typename KernelTuples::attr_type attr) {
return
GetRefer
<
KT
,
KernelTuples
>
();
}
const
char
*
to_string
(
KernelType
kt
);
}
// namespace jit
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/jit/kernel_base.h
浏览文件 @
417d031f
...
...
@@ -19,10 +19,10 @@ namespace paddle {
namespace
operators
{
namespace
jit
{
typedef
enum
{
vmul
=
0
,
vadd
=
1
,
v
sub
,
vexp
}
KernelType
;
typedef
enum
{
vmul
=
0
,
vadd
=
1
,
v
addrelu
,
vsub
,
vscal
,
vexp
}
KernelType
;
template
<
typename
T
>
struct
VMul
Tuples
{
struct
XYZN
Tuples
{
typedef
T
data_type
;
typedef
int
attr_type
;
typedef
void
(
*
func_type
)(
const
T
*
,
const
T
*
,
T
*
,
int
);
...
...
paddle/fluid/operators/jit/more/mkl/mkl.h
浏览文件 @
417d031f
...
...
@@ -28,7 +28,7 @@ template <typename T>
void
VMul
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
);
template
<
typename
T
>
class
VMulKernel
:
public
KernelImpl
<
VMul
Tuples
<
T
>>
{
class
VMulKernel
:
public
KernelImpl
<
XYZN
Tuples
<
T
>>
{
public:
VMulKernel
()
{
this
->
func
=
VMul
<
T
>
;
}
bool
UseMe
(
int
d
)
const
override
{
...
...
paddle/fluid/operators/jit/refer/refer.cc
浏览文件 @
417d031f
...
...
@@ -17,5 +17,13 @@
namespace
refer
=
paddle
::
operators
::
jit
::
refer
;
REGISTER_JITKERNEL_REFER
(
vmul
,
refer
::
VMulKernel
<
float
>
,
refer
::
VMulKernel
<
double
>
);
#define REGISTER_REFER_KERNEL(key, func) \
REGISTER_JITKERNEL_REFER(key, refer::func##Kernel<float>, \
refer::func##Kernel<double>)
REGISTER_REFER_KERNEL
(
vmul
,
VMul
);
REGISTER_REFER_KERNEL
(
vadd
,
VAdd
);
REGISTER_REFER_KERNEL
(
vaddrelu
,
VAddRelu
);
REGISTER_REFER_KERNEL
(
vsub
,
VSub
);
#undef REGISTER_REFER_KERNEL
paddle/fluid/operators/jit/refer/refer.h
浏览文件 @
417d031f
...
...
@@ -13,6 +13,7 @@
* limitations under the License. */
#pragma once
#include "paddle/fluid/operators/jit/helper.h"
#include "paddle/fluid/operators/jit/kernel_base.h"
#include "paddle/fluid/platform/enforce.h"
...
...
@@ -21,6 +22,7 @@ namespace operators {
namespace
jit
{
namespace
refer
{
// Refer code only focus on correctness
template
<
typename
T
>
void
VMul
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
...
...
@@ -29,10 +31,47 @@ void VMul(const T* x, const T* y, T* z, int n) {
}
template
<
typename
T
>
class
VMulKernel
:
public
ReferKernel
<
VMulTuples
<
T
>>
{
public:
VMulKernel
()
{
this
->
func
=
VMul
<
T
>
;
}
};
void
VAdd
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
z
[
i
]
=
x
[
i
]
+
y
[
i
];
}
}
template
<
typename
T
>
void
VAddRelu
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
z
[
i
]
=
x
[
i
]
+
y
[
i
];
z
[
i
]
=
z
[
i
]
>
0
?
z
[
i
]
:
0
;
}
}
template
<
typename
T
>
void
VSub
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
z
[
i
]
=
x
[
i
]
-
y
[
i
];
}
}
template
<
typename
T
>
void
VScal
(
const
T
*
a
,
const
T
*
x
,
T
*
y
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
y
[
i
]
=
a
[
0
]
*
x
[
i
];
}
}
#define DECLARE_REFER_KERNEL(name, tuples) \
template <typename T> \
class name##Kernel : public ReferKernel<tuples<T>> { \
public: \
name##Kernel() { this->func = name<T>; } \
}
DECLARE_REFER_KERNEL
(
VMul
,
XYZNTuples
);
DECLARE_REFER_KERNEL
(
VAdd
,
XYZNTuples
);
DECLARE_REFER_KERNEL
(
VAddRelu
,
XYZNTuples
);
DECLARE_REFER_KERNEL
(
VSub
,
XYZNTuples
);
#undef DECLARE_REFER_KERNEL
}
// namespace refer
}
// namespace jit
...
...
paddle/fluid/operators/jit/test.cc
浏览文件 @
417d031f
...
...
@@ -48,18 +48,20 @@ void ExpectEQ(const T* target, const T* refer, int n) {
std
::
vector
<
int
>
TestSizes
()
{
std
::
vector
<
int
>
s
;
for
(
int
i
=
1
;
i
<
3
0
;
++
i
)
{
for
(
int
i
=
1
;
i
<
1
0
;
++
i
)
{
s
.
push_back
(
i
);
}
// test some large size
s
.
push_back
(
100
);
s
.
push_back
(
1000
);
// // test some large size
// s.push_back(100);
// s.push_back(1000);
// s.push_back(2000);
return
s
;
}
template
<
typename
T
,
typename
Func
>
void
TestTartgetFunc
(
const
Func
tgt
,
const
std
::
vector
<
T
>&
x
,
const
std
::
vector
<
T
>&
y
,
const
std
::
vector
<
T
>&
zref
)
{
template
<
typename
T
,
typename
KernelTuples
>
void
TestTartgetFunc
(
const
typename
KernelTuples
::
func_type
tgt
,
const
std
::
vector
<
T
>&
x
,
const
std
::
vector
<
T
>&
y
,
const
std
::
vector
<
T
>&
zref
)
{
EXPECT_TRUE
(
tgt
!=
nullptr
);
EXPECT_EQ
(
zref
.
size
(),
x
.
size
());
EXPECT_EQ
(
zref
.
size
(),
y
.
size
());
...
...
@@ -83,13 +85,13 @@ void TestTartgetFunc(const Func tgt, const std::vector<T>& x,
ExpectEQ
<
T
>
(
ztgt_data
,
zref_data
,
d
);
}
TEST
(
JitKernel
,
vmul
)
{
using
T
=
float
;
using
PlaceType
=
paddle
::
platform
::
CPUPlace
;
template
<
paddle
::
operators
::
jit
::
KernelType
KT
,
typename
T
,
typename
PlaceType
>
void
TestXYZNKernel
()
{
namespace
jit
=
paddle
::
operators
::
jit
;
const
auto
KT
=
jit
::
vmul
;
for
(
int
d
:
TestSizes
())
{
auto
ref
=
jit
::
GetRefer
<
KT
,
jit
::
VMulTuples
<
T
>>
();
VLOG
(
10
)
<<
"===== Test JITKernel "
<<
jit
::
to_string
(
KT
)
<<
", size: "
<<
d
;
auto
ref
=
jit
::
GetRefer
<
KT
,
jit
::
XYZNTuples
<
T
>>
();
EXPECT_TRUE
(
ref
!=
nullptr
);
std
::
vector
<
T
>
x
(
d
),
y
(
d
),
zref
(
d
);
...
...
@@ -114,10 +116,10 @@ TEST(JitKernel, vmul) {
ExpectEQ
<
T
>
(
yinp_data
,
zref_data
,
d
);
// test jitcode
auto
jitcode
=
jit
::
GetJitCode
<
KT
,
jit
::
VMul
Tuples
<
T
>
,
PlaceType
>
(
d
);
auto
jitcode
=
jit
::
GetJitCode
<
KT
,
jit
::
XYZN
Tuples
<
T
>
,
PlaceType
>
(
d
);
if
(
jitcode
)
{
VLOG
(
10
)
<<
"Test
jitcode
, size: "
<<
d
;
TestTartgetFunc
<
T
,
jit
::
VMulTuples
<
T
>::
func_type
>
(
jitcode
,
x
,
y
,
zref
);
VLOG
(
10
)
<<
"Test
Jitcode Kernel
, size: "
<<
d
;
TestTartgetFunc
<
T
,
jit
::
XYZNTuples
<
T
>
>
(
jitcode
,
x
,
y
,
zref
);
}
// test all impls in more
...
...
@@ -127,20 +129,45 @@ TEST(JitKernel, vmul) {
if
(
iter
!=
pool
.
end
())
{
auto
&
impls
=
iter
->
second
;
for
(
auto
&
impl
:
impls
)
{
auto
i
=
dynamic_cast
<
const
jit
::
KernelImpl
<
jit
::
VMul
Tuples
<
T
>>*>
(
auto
i
=
dynamic_cast
<
const
jit
::
KernelImpl
<
jit
::
XYZN
Tuples
<
T
>>*>
(
impl
.
get
());
if
(
i
&&
i
->
UseMe
(
d
))
{
auto
more
=
i
->
GetFunc
();
VLOG
(
10
)
<<
"Test More Kernel, size: "
<<
d
;
TestTartgetFunc
<
T
,
jit
::
VMulTuples
<
T
>::
func_type
>
(
more
,
x
,
y
,
zref
);
TestTartgetFunc
<
T
,
jit
::
XYZNTuples
<
T
>
>
(
more
,
x
,
y
,
zref
);
}
}
}
// Test result from Get function
VLOG
(
10
)
<<
"Test Get function, size: "
<<
d
;
auto
tgt
=
jit
::
Get
<
KT
,
jit
::
VMul
Tuples
<
T
>
,
PlaceType
>
(
d
);
TestTartgetFunc
<
T
,
jit
::
VMulTuples
<
T
>::
func_type
>
(
tgt
,
x
,
y
,
zref
);
auto
tgt
=
jit
::
Get
<
KT
,
jit
::
XYZN
Tuples
<
T
>
,
PlaceType
>
(
d
);
TestTartgetFunc
<
T
,
jit
::
XYZNTuples
<
T
>
>
(
tgt
,
x
,
y
,
zref
);
}
}
TEST
(
JitKernel
,
pool
)
{}
TEST
(
JITKernel
,
vmul
)
{
namespace
jit
=
paddle
::
operators
::
jit
;
TestXYZNKernel
<
jit
::
vmul
,
float
,
paddle
::
platform
::
CPUPlace
>
();
// TODO(TJ): fix double issue
// TestXYZNKernel<jit::vmul, double, paddle::platform::CPUPlace>();
}
TEST
(
JITKernel
,
vadd
)
{
namespace
jit
=
paddle
::
operators
::
jit
;
TestXYZNKernel
<
jit
::
vadd
,
float
,
paddle
::
platform
::
CPUPlace
>
();
TestXYZNKernel
<
jit
::
vadd
,
double
,
paddle
::
platform
::
CPUPlace
>
();
}
TEST
(
JITKernel
,
vaddrelu
)
{
namespace
jit
=
paddle
::
operators
::
jit
;
TestXYZNKernel
<
jit
::
vaddrelu
,
float
,
paddle
::
platform
::
CPUPlace
>
();
TestXYZNKernel
<
jit
::
vaddrelu
,
double
,
paddle
::
platform
::
CPUPlace
>
();
}
TEST
(
JITKernel
,
vsub
)
{
namespace
jit
=
paddle
::
operators
::
jit
;
TestXYZNKernel
<
jit
::
vsub
,
float
,
paddle
::
platform
::
CPUPlace
>
();
TestXYZNKernel
<
jit
::
vsub
,
double
,
paddle
::
platform
::
CPUPlace
>
();
}
TEST
(
JITKernel
,
pool
)
{}
paddle/fluid/operators/math/jit_kernel_refer.h
浏览文件 @
417d031f
...
...
@@ -23,36 +23,6 @@ namespace operators {
namespace
math
{
namespace
jitkernel
{
namespace
refer
{
/* Refer code only focus on correctness */
template
<
typename
T
>
void
VMul
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
z
[
i
]
=
x
[
i
]
*
y
[
i
];
}
}
template
<
typename
T
>
void
VAdd
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
z
[
i
]
=
x
[
i
]
+
y
[
i
];
}
}
template
<
typename
T
>
void
VAddRelu
(
const
T
*
x
,
const
T
*
y
,
T
*
z
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
z
[
i
]
=
x
[
i
]
+
y
[
i
];
z
[
i
]
=
z
[
i
]
>
0
?
z
[
i
]
:
0
;
}
}
template
<
typename
T
>
void
VScal
(
const
T
*
a
,
const
T
*
x
,
T
*
y
,
int
n
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
y
[
i
]
=
a
[
0
]
*
x
[
i
];
}
}
template
<
typename
T
>
void
VAddBias
(
const
T
*
a
,
const
T
*
x
,
T
*
y
,
int
n
)
{
...
...
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