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体验新版 GitCode,发现更多精彩内容 >>
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7383eefd
编写于
1月 28, 2019
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 softmax mix and mkl code
test=develop
上级
50945685
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
74 addition
and
0 deletion
+74
-0
paddle/fluid/operators/jit/more/mix/CMakeLists.txt
paddle/fluid/operators/jit/more/mix/CMakeLists.txt
+1
-0
paddle/fluid/operators/jit/more/mix/mix.cc
paddle/fluid/operators/jit/more/mix/mix.cc
+24
-0
paddle/fluid/operators/jit/more/mix/mix.h
paddle/fluid/operators/jit/more/mix/mix.h
+4
-0
paddle/fluid/operators/jit/more/mkl/CMakeLists.txt
paddle/fluid/operators/jit/more/mkl/CMakeLists.txt
+1
-0
paddle/fluid/operators/jit/more/mkl/mkl.cc
paddle/fluid/operators/jit/more/mkl/mkl.cc
+17
-0
paddle/fluid/operators/jit/more/mkl/mkl.h
paddle/fluid/operators/jit/more/mkl/mkl.h
+27
-0
未找到文件。
paddle/fluid/operators/jit/more/mix/CMakeLists.txt
浏览文件 @
7383eefd
...
...
@@ -12,3 +12,4 @@ USE_JITKERNEL_MORE(kLSTMC1H1, mix)
USE_JITKERNEL_MORE
(
kGRUH1, mix
)
USE_JITKERNEL_MORE
(
kGRUHtPart1, mix
)
USE_JITKERNEL_MORE
(
kGRUHtPart2, mix
)
USE_JITKERNEL_MORE
(
kSoftmax, mix
)
paddle/fluid/operators/jit/more/mix/mix.cc
浏览文件 @
7383eefd
...
...
@@ -48,6 +48,27 @@ void VTanh(const T* x, T* y, int n) {
compute_addbias
(
&
b
,
y
,
y
,
n
);
}
void
Softmax
(
const
T
*
x
,
T
*
y
,
int
n
,
int
bs
)
{
auto
compute_hmax
=
Get
<
kHMax
,
XRNTuples
<
T
>
,
platform
::
CPUPlace
>
(
n
);
auto
compute_hsum
=
Get
<
kHSum
,
XRNTuples
<
T
>
,
platform
::
CPUPlace
>
(
n
);
auto
compute_vscal
=
Get
<
kVScal
,
AXYNTuples
<
T
>
,
platform
::
CPUPlace
>
(
n
);
auto
compute_vaddbias
=
Get
<
kVAddBias
,
AXYNTuples
<
T
>
,
platform
::
CPUPlace
>
(
n
);
auto
compute_vexp
=
Get
<
KernelType
::
kVExp
,
XYNTuples
<
T
>
,
platform
::
CPUPlace
>
(
n
);
for
(
int
i
=
0
;
i
<
bs
;
++
i
)
{
T
scalar
;
compute_hmax
(
x
,
&
scalar
,
n
);
scalar
=
static_cast
<
T
>
(
0
)
-
scalar
;
compute_vaddbias
(
&
scalar
,
x
,
y
,
n
);
// x - max
compute_vexp
(
y
,
y
,
n
);
compute_hsum
(
y
,
&
scalar
,
n
);
scalar
=
static_cast
<
T
>
(
1
)
/
scalar
;
compute_vscal
(
&
scalar
,
y
,
y
,
n
);
x
+=
n
;
y
+=
n
;
}
}
void
(
*
getActFunc
(
KernelType
type
,
int
d
))(
const
T
*
,
T
*
,
int
)
{
// NOLINT
if
(
type
==
kVSigmoid
)
{
return
Get
<
kVSigmoid
,
XYNTuples
<
T
>
,
platform
::
CPUPlace
>
(
d
);
...
...
@@ -184,6 +205,8 @@ bool VSigmoidKernel::UseMe(const int& d) const { return true; }
bool
VTanhKernel
::
UseMe
(
const
int
&
d
)
const
{
return
true
;
}
bool
SoftmaxKernel
::
UseMe
(
const
int
&
d
)
const
{
return
true
;
}
bool
LSTMCtHtKernel
::
UseMe
(
const
lstm_attr_t
&
attr
)
const
{
return
true
;
}
bool
LSTMC1H1Kernel
::
UseMe
(
const
lstm_attr_t
&
attr
)
const
{
return
true
;
}
...
...
@@ -207,6 +230,7 @@ namespace mix = paddle::operators::jit::more::mix;
REGISTER_MORE_KERNEL
(
kVSigmoid
,
VSigmoid
);
REGISTER_MORE_KERNEL
(
kVTanh
,
VTanh
);
REGISTER_MORE_KERNEL
(
kSoftmax
,
Softmax
);
REGISTER_MORE_KERNEL
(
kLSTMCtHt
,
LSTMCtHt
);
REGISTER_MORE_KERNEL
(
kLSTMC1H1
,
LSTMC1H1
);
REGISTER_MORE_KERNEL
(
kGRUH1
,
GRUH1
);
...
...
paddle/fluid/operators/jit/more/mix/mix.h
浏览文件 @
7383eefd
...
...
@@ -26,6 +26,7 @@ using T = float;
void
VSigmoid
(
const
T
*
x
,
T
*
y
,
int
n
);
void
VTanh
(
const
T
*
x
,
T
*
y
,
int
n
);
void
Softmax
(
const
T
*
x
,
T
*
y
,
int
n
,
int
bs
);
void
LSTMCtHt
(
lstm_t
*
step
,
const
lstm_attr_t
*
attr
);
void
LSTMC1H1
(
lstm_t
*
step
,
const
lstm_attr_t
*
attr
);
...
...
@@ -45,6 +46,9 @@ void GRUHtPart2(gru_t* step, const gru_attr_t* attr);
DECLARE_MORE_KERNEL
(
VSigmoid
,
XYNTuples
);
DECLARE_MORE_KERNEL
(
VTanh
,
XYNTuples
);
// XRN
DECLARE_MORE_KERNEL
(
Softmax
,
SoftmaxTuples
);
DECLARE_MORE_KERNEL
(
LSTMCtHt
,
LSTMTuples
);
DECLARE_MORE_KERNEL
(
LSTMC1H1
,
LSTMTuples
);
...
...
paddle/fluid/operators/jit/more/mkl/CMakeLists.txt
浏览文件 @
7383eefd
...
...
@@ -12,3 +12,4 @@ USE_JITKERNEL_MORE(kVSquare, mkl)
USE_JITKERNEL_MORE
(
kVSigmoid, mkl
)
USE_JITKERNEL_MORE
(
kVTanh, mkl
)
USE_JITKERNEL_MORE
(
kSeqPool, mkl
)
USE_JITKERNEL_MORE
(
kSoftmax, mkl
)
paddle/fluid/operators/jit/more/mkl/mkl.cc
浏览文件 @
7383eefd
...
...
@@ -116,6 +116,16 @@ void VAXPY<double>(double a, const double* x, double* y, int n) {
platform
::
dynload
::
cblas_daxpy
(
n
,
a
,
x
,
1
,
y
,
1
);
}
template
<
>
void
ASum
<
float
>
(
const
float
*
x
,
float
*
res
,
int
n
)
{
res
[
0
]
=
platform
::
dynload
::
cblas_sasum
(
n
,
x
,
1
);
}
template
<
>
void
ASum
<
double
>
(
const
double
*
x
,
double
*
res
,
int
n
)
{
res
[
0
]
=
platform
::
dynload
::
cblas_dasum
(
n
,
x
,
1
);
}
// TODO(TJ): tuning me carefully on AVX, AVX2 and AVX512
template
<
>
bool
MatMulKernel
<
float
>::
UseMe
(
const
int
&
d
)
const
{
...
...
@@ -167,6 +177,11 @@ bool SeqPoolKernel<double>::UseMe(const seq_pool_attr_t& attr) const {
return
true
;
}
template
<
>
bool
SoftmaxKernel
<
float
>::
UseMe
(
const
int
&
d
)
const
{
return
true
;
}
#define AWALYS_USE_ME_WITH_DOUBLE(func) \
template <> \
bool func##Kernel<double>::UseMe(const int& d) const { \
...
...
@@ -181,6 +196,7 @@ AWALYS_USE_ME_WITH_DOUBLE(VExp);
AWALYS_USE_ME_WITH_DOUBLE
(
VSigmoid
);
AWALYS_USE_ME_WITH_DOUBLE
(
VTanh
);
AWALYS_USE_ME_WITH_DOUBLE
(
VSquare
);
AWALYS_USE_ME_WITH_DOUBLE
(
Softmax
);
#undef AWALYS_USE_ME_WITH_DOUBLE
}
// namespace mkl
...
...
@@ -204,5 +220,6 @@ REGISTER_MKL_KERNEL(kVSquare, VSquare);
REGISTER_MKL_KERNEL
(
kVSigmoid
,
VSigmoid
);
REGISTER_MKL_KERNEL
(
kVTanh
,
VTanh
);
REGISTER_MKL_KERNEL
(
kSeqPool
,
SeqPool
);
REGISTER_MKL_KERNEL
(
kSoftmax
,
Softmax
);
#undef REGISTER_MKL_KERNEL
paddle/fluid/operators/jit/more/mkl/mkl.h
浏览文件 @
7383eefd
...
...
@@ -16,6 +16,7 @@
#include <cmath>
#include <type_traits>
#include <vector>
#include "paddle/fluid/operators/jit/kernel_base.h"
namespace
paddle
{
...
...
@@ -90,6 +91,30 @@ void SeqPool(const T* x, T* y, const seq_pool_attr_t* attr) {
}
}
template
<
typename
T
>
void
ASum
(
const
T
*
x
,
T
*
res
,
int
n
);
template
<
typename
T
>
void
Softmax
(
const
T
*
x
,
T
*
y
,
int
n
,
int
bs
)
{
std
::
vector
<
T
>
entities
(
bs
);
for
(
int
i
=
0
;
i
<
bs
;
++
i
)
{
entities
[
i
]
=
x
[
i
*
n
];
for
(
int
c
=
1
;
c
<
n
;
++
c
)
{
entities
[
i
]
=
x
[
i
*
n
+
c
]
>
entities
[
i
]
?
x
[
i
*
n
+
c
]
:
entities
[
i
];
}
for
(
int
c
=
0
;
c
<
n
;
++
c
)
{
y
[
i
*
n
+
c
]
=
x
[
i
*
n
+
c
]
-
entities
[
i
];
}
}
VExp
(
y
,
y
,
n
*
bs
);
for
(
int
i
=
0
;
i
<
bs
;
++
i
)
{
T
sum
;
ASum
(
&
y
[
i
*
n
],
&
sum
,
n
);
sum
=
static_cast
<
T
>
(
1
)
/
sum
;
VScal
(
&
sum
,
&
y
[
i
*
n
],
&
y
[
i
*
n
],
n
);
}
}
#define DECLARE_MKL_KERNEL(name, tuples) \
template <typename T> \
class name##Kernel : public KernelMore<tuples<T>> { \
...
...
@@ -117,6 +142,8 @@ DECLARE_MKL_KERNEL(VSquare, XYNTuples);
DECLARE_MKL_KERNEL
(
SeqPool
,
SeqPoolTuples
);
DECLARE_MKL_KERNEL
(
Softmax
,
SoftmaxTuples
);
#undef DECLARE_MKL_KERNEL
}
// namespace mkl
...
...
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