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53b0e427
编写于
8月 17, 2017
作者:
H
hedaoyuan
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
Add EigenGemm.
上级
9eaef753
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
211 addition
and
65 deletion
+211
-65
paddle/function/EigenGemm.cpp
paddle/function/EigenGemm.cpp
+92
-0
paddle/function/GemmFunctor.cpp
paddle/function/GemmFunctor.cpp
+85
-0
paddle/function/GemmFunctor.h
paddle/function/GemmFunctor.h
+34
-65
未找到文件。
paddle/function/EigenGemm.cpp
0 → 100644
浏览文件 @
53b0e427
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 <glog/logging.h>
#include "unsupported/Eigen/CXX11/Tensor"
namespace
paddle
{
template
<
class
T
>
struct
EigenBlasGemm
{
typedef
Eigen
::
TensorMap
<
Eigen
::
Tensor
<
T
,
2
,
Eigen
::
RowMajor
,
int
>
,
Eigen
::
Aligned
>
Matrix
;
static
void
compute
(
const
bool
transA
,
const
bool
transB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
)
{
Eigen
::
array
<
int
,
2
>
sizeA
;
if
(
transA
)
{
sizeA
[
0
]
=
K
;
sizeA
[
1
]
=
M
;
CHECK_EQ
(
M
,
lda
);
}
else
{
sizeA
[
0
]
=
M
;
sizeA
[
1
]
=
K
;
CHECK_EQ
(
K
,
lda
);
}
Eigen
::
array
<
int
,
2
>
sizeB
;
if
(
transB
)
{
sizeB
[
0
]
=
N
;
sizeB
[
1
]
=
K
;
CHECK_EQ
(
K
,
ldb
);
}
else
{
sizeB
[
0
]
=
K
;
sizeB
[
1
]
=
N
;
CHECK_EQ
(
N
,
ldb
);
}
Eigen
::
array
<
int
,
2
>
sizeC
;
sizeC
[
0
]
=
M
;
sizeC
[
1
]
=
N
;
CHECK_EQ
(
N
,
ldc
);
const
Matrix
a
(
const_cast
<
T
*>
(
A
),
sizeA
);
const
Matrix
b
(
const_cast
<
T
*>
(
B
),
sizeB
);
Matrix
c
(
C
,
sizeC
);
typedef
typename
Eigen
::
Tensor
<
T
,
2
>::
DimensionPair
DimPair
;
Eigen
::
array
<
DimPair
,
1
>
dims
;
dims
[
0
]
=
DimPair
(
1
,
0
);
dims
[
0
].
first
=
transA
?
0
:
1
;
dims
[
0
].
second
=
transB
?
1
:
0
;
Eigen
::
DefaultDevice
device
;
if
(
alpha
==
T
(
1
)
&&
beta
==
T
(
0
))
{
c
.
device
(
device
)
=
a
.
contract
(
b
,
dims
);
}
else
if
(
alpha
==
T
(
1
)
&&
beta
==
T
(
1
))
{
c
.
device
(
device
)
+=
a
.
contract
(
b
,
dims
);
}
else
{
c
.
device
(
device
)
=
c
.
constant
(
alpha
)
*
a
.
contract
(
b
,
dims
)
+
c
.
constant
(
beta
)
*
c
;
}
}
};
#ifdef PADDLE_TYPE_DOUBLE
template
class
EigenBlasGemm
<
double
>;
#else
template
class
EigenBlasGemm
<
float
>;
#endif
}
// namespace paddle
paddle/function/GemmFunctor.cpp
0 → 100644
浏览文件 @
53b0e427
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 "GemmFunctor.h"
#include "paddle/math/MathFunctions.h"
namespace
paddle
{
template
<
class
T
>
struct
BlasGemm
<
DEVICE_TYPE_CPU
,
T
>
{
static
void
compute
(
const
bool
transA
,
const
bool
transB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
)
{
gemm
<
T
>
(
transA
==
false
?
CblasNoTrans
:
CblasTrans
,
transB
==
false
?
CblasNoTrans
:
CblasTrans
,
M
,
N
,
K
,
alpha
,
A
,
lda
,
B
,
ldb
,
beta
,
C
,
ldc
);
}
};
template
<
class
T
>
struct
BlasGemm
<
DEVICE_TYPE_GPU
,
T
>
{
static
void
compute
(
const
bool
transA
,
const
bool
transB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
)
{
hl_matrix_mul
((
T
*
)
A
,
transA
==
false
?
HPPL_OP_N
:
HPPL_OP_T
,
(
T
*
)
B
,
transB
==
false
?
HPPL_OP_N
:
HPPL_OP_T
,
C
,
M
,
N
,
K
,
alpha
,
beta
,
lda
,
ldb
,
ldc
);
}
};
template
class
BlasGemm
<
DEVICE_TYPE_CPU
,
real
>;
template
class
BlasGemm
<
DEVICE_TYPE_GPU
,
real
>;
}
// namespace paddle
paddle/function/GemmFunctor.h
浏览文件 @
53b0e427
...
...
@@ -14,7 +14,7 @@ limitations under the License. */
#pragma once
#include "
paddle/math/MathFunctions
.h"
#include "
TensorType
.h"
namespace
paddle
{
...
...
@@ -24,73 +24,42 @@ namespace paddle {
// of MatMulFunction, we need to consider the reconstruction of hl_matrix_mul
// interface.
template
<
DeviceType
Device
,
class
T
>
class
GemmFunctor
{
public:
void
operator
()(
const
CBLAS_TRANSPOSE
transA
,
const
CBLAS_TRANSPOSE
TransB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
);
struct
BlasGemm
{
static
void
compute
(
const
bool
transA
,
const
bool
transB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
);
};
// TODO(hedaoyuan): Since the definition of the real type in the Paddle
// conflicts with the Eigen library, so compile the Eigen code can not
// include the Paddle header file. And need an EigenBlasGemm template class
// that does not contain the DeviceType parameter.
// I will fix this problem and merge BlasGemm and EigenBlasGemm into one.
template
<
class
T
>
class
GemmFunctor
<
DEVICE_TYPE_CPU
,
T
>
{
public:
void
operator
()(
const
CBLAS_TRANSPOSE
transA
,
const
CBLAS_TRANSPOSE
TransB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
)
{
gemm
<
T
>
(
transA
,
TransB
,
M
,
N
,
K
,
alpha
,
A
,
lda
,
B
,
ldb
,
beta
,
C
,
ldc
);
}
};
template
<
class
T
>
class
GemmFunctor
<
DEVICE_TYPE_GPU
,
T
>
{
public:
void
operator
()(
const
CBLAS_TRANSPOSE
transA
,
const
CBLAS_TRANSPOSE
TransB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
)
{
hl_matrix_mul
((
T
*
)
A
,
transA
==
CblasNoTrans
?
HPPL_OP_N
:
HPPL_OP_T
,
(
T
*
)
B
,
TransB
==
CblasNoTrans
?
HPPL_OP_N
:
HPPL_OP_T
,
C
,
M
,
N
,
K
,
alpha
,
beta
,
lda
,
ldb
,
ldc
);
}
struct
EigenBlasGemm
{
static
void
compute
(
const
bool
transA
,
const
bool
transB
,
const
int
M
,
const
int
N
,
const
int
K
,
const
T
alpha
,
const
T
*
A
,
const
int
lda
,
const
T
*
B
,
const
int
ldb
,
const
T
beta
,
T
*
C
,
const
int
ldc
);
};
}
// namespace paddle
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