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9ade63e6
编写于
1月 18, 2017
作者:
X
xutianbing
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
clean code a little bit.
上级
171eaff2
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
72 addition
and
152 deletion
+72
-152
paddle/function/MulOp.cpp
paddle/function/MulOp.cpp
+72
-152
未找到文件。
paddle/function/MulOp.cpp
浏览文件 @
9ade63e6
...
@@ -56,7 +56,16 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
...
@@ -56,7 +56,16 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
/// todo(tianbing), clean the code
/// todo(tianbing), clean the code
CHECK
(
!
out
.
isTransposed
())
<<
"Not supported"
;
CHECK
(
!
out
.
isTransposed
())
<<
"Not supported"
;
CHECK_EQ
(
out
.
getValueType
(),
FLOAT_VALUE
);
CHECK_EQ
(
out
.
getValueType
(),
FLOAT_VALUE
);
CHECK
(
!
a
.
isTransposed
()
||
!
b
.
isTransposed
())
<<
"Not support both a and b are transpose matrices"
;
if
(
!
a
.
isTransposed
()
&&
b
.
isTransposed
())
{
CHECK
(
out
.
getFormat
()
!=
SPARSE_CSC
)
<<
"Not supported CSC format when a is not trans and b is trans"
;
}
if
(
scaleT
==
0
)
{
out
.
zeroMem
();
}
const
real
*
A
=
a
.
getData
();
const
real
*
A
=
a
.
getData
();
const
real
*
B
=
b
.
getData
();
const
real
*
B
=
b
.
getData
();
real
*
C
=
out
.
getValue
();
real
*
C
=
out
.
getValue
();
...
@@ -64,15 +73,11 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
...
@@ -64,15 +73,11 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
int
*
cols
=
out
.
getCols
();
int
*
cols
=
out
.
getCols
();
size_t
height
=
out
.
getHeight
();
size_t
height
=
out
.
getHeight
();
size_t
width
=
out
.
getWidth
();
size_t
width
=
out
.
getWidth
();
if
(
scaleT
==
0
)
{
out
.
zeroMem
();
}
if
(
!
a
.
isTransposed
()
&&
!
b
.
isTransposed
())
{
if
(
!
a
.
isTransposed
()
&&
!
b
.
isTransposed
())
{
CHECK
(
b
.
getHeight
()
==
a
.
getWidth
()
&&
a
.
getHeight
()
==
height
&&
b
.
getWidth
()
==
width
);
size_t
m
=
a
.
getWidth
();
size_t
m
=
a
.
getWidth
();
CHECK_EQ
(
b
.
getHeight
(),
m
);
CHECK_EQ
(
a
.
getHeight
(),
height
);
CHECK_EQ
(
b
.
getWidth
(),
width
);
if
(
out
.
getFormat
()
==
SPARSE_CSC
)
{
if
(
out
.
getFormat
()
==
SPARSE_CSC
)
{
for
(
size_t
i
=
0
;
i
<
width
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
width
;
i
++
)
{
size_t
start
=
out
.
getColStartIdx
(
i
);
size_t
start
=
out
.
getColStartIdx
(
i
);
...
@@ -86,26 +91,27 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
...
@@ -86,26 +91,27 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
}
}
}
}
}
else
{
}
else
{
/// out.getFormat() == SPARSE_CSR
for
(
size_t
i
=
0
;
i
<
height
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
height
;
i
++
)
{
size_t
start
=
out
.
getRowStartIdx
(
i
);
size_t
start
=
out
.
getRowStartIdx
(
i
);
size_t
end
=
out
.
getRowStartIdx
(
i
+
1
);
size_t
end
=
out
.
getRowStartIdx
(
i
+
1
);
for
(
size_t
j
=
start
;
j
<
end
;
j
++
)
{
for
(
size_t
j
=
start
;
j
<
end
;
j
++
)
{
real
sum
=
0
;
real
sum
=
0
;
size_t
colIdx
=
cols
[
j
];
size_t
colIdx
=
cols
[
j
];
for
(
size_t
k
=
0
;
k
<
m
;
k
++
)
{
for
(
size_t
k
=
0
;
k
<
a
.
getWidth
()
;
k
++
)
{
sum
+=
A
[
i
*
m
+
k
]
*
B
[
k
*
width
+
colIdx
];
sum
+=
A
[
i
*
m
+
k
]
*
B
[
k
*
width
+
colIdx
];
}
}
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
}
}
}
}
}
}
}
else
if
(
a
.
isTransposed
()
&&
!
b
.
isTransposed
())
{
return
;
size_t
m
=
a
.
getHeight
();
}
CHECK_EQ
(
m
,
b
.
getHeight
());
CHECK_EQ
(
b
.
getWidth
(),
width
);
CHECK_EQ
(
a
.
getWidth
(),
height
);
if
(
a
.
isTransposed
()
&&
!
b
.
isTransposed
())
{
CHECK
(
a
.
getHeight
()
==
b
.
getHeight
()
&&
b
.
getWidth
()
==
width
&&
a
.
getWidth
()
==
height
);
size_t
m
=
a
.
getHeight
();
if
(
out
.
getFormat
()
==
SPARSE_CSC
)
{
if
(
out
.
getFormat
()
==
SPARSE_CSC
)
{
for
(
size_t
i
=
0
;
i
<
width
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
width
;
i
++
)
{
size_t
start
=
out
.
getColStartIdx
(
i
);
size_t
start
=
out
.
getColStartIdx
(
i
);
...
@@ -119,25 +125,27 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
...
@@ -119,25 +125,27 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
}
}
}
}
}
else
{
}
else
{
/// out.getFormat() == SPARSE_CSR
for
(
size_t
i
=
0
;
i
<
height
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
height
;
i
++
)
{
int
start
=
out
.
getRowStartIdx
(
i
);
int
start
=
out
.
getRowStartIdx
(
i
);
int
end
=
out
.
getRowStartIdx
(
i
+
1
);
int
end
=
out
.
getRowStartIdx
(
i
+
1
);
for
(
int
j
=
start
;
j
<
end
;
j
++
)
{
for
(
int
j
=
start
;
j
<
end
;
j
++
)
{
real
sum
=
0
;
real
sum
=
0
;
size_t
colIdx
=
cols
[
j
];
size_t
colIdx
=
cols
[
j
];
for
(
size_t
k
=
0
;
k
<
m
;
k
++
)
{
for
(
size_t
k
=
0
;
k
<
a
.
getHeight
()
;
k
++
)
{
sum
+=
A
[
k
*
height
+
i
]
*
B
[
k
*
width
+
colIdx
];
sum
+=
A
[
k
*
height
+
i
]
*
B
[
k
*
width
+
colIdx
];
}
}
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
}
}
}
}
}
}
}
else
if
(
!
a
.
isTransposed
()
&&
b
.
isTransposed
())
{
return
;
}
if
(
!
a
.
isTransposed
()
&&
b
.
isTransposed
())
{
CHECK
(
b
.
getWidth
()
==
a
.
getWidth
()
&&
a
.
getHeight
()
==
height
&&
b
.
getHeight
()
==
width
);
size_t
m
=
a
.
getWidth
();
size_t
m
=
a
.
getWidth
();
CHECK_EQ
(
b
.
getWidth
(),
m
);
CHECK_EQ
(
a
.
getHeight
(),
height
);
CHECK_EQ
(
b
.
getHeight
(),
width
);
if
(
out
.
getFormat
()
==
SPARSE_CSR
)
{
if
(
out
.
getFormat
()
==
SPARSE_CSR
)
{
for
(
size_t
i
=
0
;
i
<
height
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
height
;
i
++
)
{
size_t
start
=
out
.
getRowStartIdx
(
i
);
size_t
start
=
out
.
getRowStartIdx
(
i
);
...
@@ -151,12 +159,8 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
...
@@ -151,12 +159,8 @@ void MulOp<DEVICE_TYPE_CPU>(CpuSparseMatrix& out,
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
C
[
j
]
=
scaleAB
*
sum
+
scaleT
*
C
[
j
];
}
}
}
}
}
else
{
LOG
(
FATAL
)
<<
"Not supported csc format "
"when a is not trans and b is trans"
;
}
}
}
else
{
return
;
LOG
(
FATAL
)
<<
"Not supported"
;
}
}
}
}
...
@@ -166,159 +170,75 @@ void MulOp<DEVICE_TYPE_CPU>(CpuMatrix& out,
...
@@ -166,159 +170,75 @@ void MulOp<DEVICE_TYPE_CPU>(CpuMatrix& out,
const
CpuMatrix
&
b
,
const
CpuMatrix
&
b
,
real
scaleAB
,
real
scaleAB
,
real
scaleT
)
{
real
scaleT
)
{
/// todo(tianbing), clean the code
CHECK
(
!
out
.
isTransposed
())
<<
"out matrix transpose not supported"
;
CHECK
(
!
out
.
isTransposed
())
<<
"Not supported"
;
CBLAS_TRANSPOSE
aTrans
=
a
.
isTransposed
()
?
CblasTrans
:
CblasNoTrans
;
CBLAS_TRANSPOSE
aTrans
=
CblasNoTrans
;
size_t
aRow
=
a
.
isTransposed
()
?
a
.
getWidth
()
:
a
.
getHeight
();
size_t
aRow
=
a
.
getHeight
();
size_t
aCol
=
a
.
isTransposed
()
?
a
.
getHeight
()
:
a
.
getWidth
();
size_t
aCol
=
a
.
getWidth
();
CBLAS_TRANSPOSE
bTrans
=
b
.
isTransposed
()
?
CblasTrans
:
CblasNoTrans
;
CBLAS_TRANSPOSE
bTrans
=
CblasNoTrans
;
size_t
bRow
=
b
.
isTransposed
()
?
b
.
getWidth
()
:
b
.
getHeight
();
size_t
bRow
=
b
.
getHeight
();
size_t
bCol
=
b
.
isTransposed
()
?
b
.
getHeight
()
:
b
.
getWidth
();
size_t
bCol
=
b
.
getWidth
();
if
(
a
.
isTransposed
())
{
aTrans
=
CblasTrans
;
aRow
=
a
.
getWidth
();
aCol
=
a
.
getHeight
();
}
if
(
b
.
isTransposed
())
{
bTrans
=
CblasTrans
;
bRow
=
b
.
getWidth
();
bCol
=
b
.
getHeight
();
}
/// C = A * B, for matrix format
/// C = A * B, for matrix format
CHECK_EQ
(
aCol
,
bRow
);
CHECK_EQ
(
aCol
,
bRow
);
CHECK_EQ
(
aRow
,
out
.
getHeight
());
CHECK_EQ
(
aRow
,
out
.
getHeight
());
CHECK_EQ
(
bCol
,
out
.
getWidth
());
CHECK_EQ
(
bCol
,
out
.
getWidth
());
const
real
*
A
=
a
.
getData
();
GEMM
(
aTrans
,
const
real
*
B
=
b
.
getData
();
bTrans
,
real
*
C
=
out
.
getData
();
out
.
getHeight
(),
out
.
getWidth
(),
int
M
=
out
.
getHeight
();
aCol
,
int
N
=
out
.
getWidth
();
scaleAB
,
int
K
=
aCol
;
a
.
getData
(),
int
lda
=
a
.
getStride
();
a
.
getStride
(),
int
ldb
=
b
.
getStride
();
b
.
getData
(),
int
ldc
=
out
.
getStride
();
b
.
getStride
(),
scaleT
,
GEMM
(
aTrans
,
bTrans
,
M
,
N
,
K
,
scaleAB
,
A
,
lda
,
B
,
ldb
,
scaleT
,
C
,
ldc
);
out
.
getData
(),
out
.
getStride
());
VLOG
(
2
)
<<
" A[0]="
<<
A
[
0
]
<<
" A[1]="
<<
A
[
1
]
<<
" B[0]="
<<
B
[
0
]
<<
" B[1]="
<<
B
[
1
]
<<
" C[0]="
<<
C
[
0
]
<<
" C[1]="
<<
C
[
1
];
}
}
static
ThreadLocal
<
std
::
vector
<
const
real
*>>
threadLocalColArray
;
template
<
>
template
<
>
void
MulOp
<
DEVICE_TYPE_CPU
>
(
CpuMatrix
&
out
,
void
MulOp
<
DEVICE_TYPE_CPU
>
(
CpuMatrix
&
out
,
const
CpuSparseMatrix
&
a
,
const
CpuSparseMatrix
&
a
,
const
CpuMatrix
&
b
,
const
CpuMatrix
&
b
,
real
scaleAB
,
real
scaleAB
,
real
scaleT
)
{
real
scaleT
)
{
/// todo(tianbing), clean the code
CHECK
(
!
out
.
isTransposed
())
<<
"Not supported"
;
CHECK
(
!
out
.
isTransposed
())
<<
"Not supported"
;
CHECK
(
!
b
.
isTransposed
())
<<
"Not supported"
;
CHECK
(
!
b
.
isTransposed
())
<<
"Not supported"
;
CHECK
(
scaleT
==
0
||
scaleT
==
1
)
<<
"Not support"
;
CHECK
(
scaleT
==
0
||
scaleT
==
1
)
<<
"Not support"
;
CHECK_EQ
(
scaleAB
,
static_cast
<
real
>
(
1.0
))
<<
"Not supported"
;
CHECK_EQ
(
scaleAB
,
static_cast
<
real
>
(
1.0
))
<<
"Not supported"
;
CHECK_EQ
(
a
.
getFormat
(),
SPARSE_CSR
)
<<
"Not supported"
;
CHECK_EQ
(
a
.
getFormat
(),
SPARSE_CSR
)
<<
"Not supported"
;
const
real
*
B
=
b
.
getData
();
if
(
!
a
.
isTransposed
())
{
real
*
C
=
out
.
getData
();
CHECK
(
b
.
getHeight
()
==
a
.
getWidth
()
&&
a
.
getHeight
()
==
out
.
getHeight
()
&&
size_t
height
=
out
.
getHeight
();
b
.
getWidth
()
==
out
.
getWidth
());
size_t
width
=
out
.
getWidth
();
}
else
{
int
*
cols
=
a
.
getCols
();
CHECK
(
b
.
getHeight
()
==
a
.
getHeight
()
&&
a
.
getWidth
()
==
out
.
getHeight
()
&&
real
*
values
=
a
.
getValue
();
b
.
getWidth
()
==
out
.
getWidth
());
}
if
(
scaleT
==
0
)
{
if
(
scaleT
==
0
)
{
out
.
zeroMem
();
out
.
zeroMem
();
}
}
const
real
*
B
=
b
.
getData
();
real
*
C
=
out
.
getData
();
if
(
out
.
getWidth
()
%
32
==
0
)
{
CHECK_EQ
((
size_t
)
B
%
32
,
0UL
);
CHECK_EQ
((
size_t
)
C
%
32
,
0UL
);
}
if
(
!
a
.
isTransposed
())
{
int
*
cols
=
a
.
getCols
();
size_t
m
=
a
.
getWidth
();
real
*
values
=
a
.
getValue
();
CHECK_EQ
(
b
.
getHeight
(),
m
);
for
(
size_t
i
=
0
;
i
<
a
.
getHeight
();
++
i
)
{
CHECK_EQ
(
a
.
getHeight
(),
height
);
const
int
start
=
a
.
getRowStartIdx
(
i
);
CHECK_EQ
(
b
.
getWidth
(),
width
);
const
int
end
=
a
.
getRowStartIdx
(
i
+
1
);
for
(
int
j
=
start
;
j
<
end
;
++
j
)
{
if
(
a
.
getValueType
()
==
NO_VALUE
)
{
vecAddTo
(
!
a
.
isTransposed
()
?
out
.
getRow
(
i
)
:
out
.
getRow
(
cols
[
j
]),
if
(
width
%
32
==
0
)
{
// use libaddto
!
a
.
isTransposed
()
?
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
cols
[
j
])
CHECK_EQ
((
size_t
)
B
%
32
,
0UL
);
:
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
i
),
CHECK_EQ
((
size_t
)
C
%
32
,
0UL
);
(
a
.
getValueType
()
==
FLOAT_VALUE
)
?
values
[
j
]
:
(
real
)
1.0
,
auto
&
colArray
=
*
threadLocalColArray
;
out
.
getWidth
());
for
(
size_t
i
=
0
;
i
<
a
.
getHeight
();
++
i
)
{
const
int
start
=
a
.
getRowStartIdx
(
i
);
const
int
end
=
a
.
getRowStartIdx
(
i
+
1
);
size_t
colNum
=
end
-
start
;
colArray
.
resize
(
colNum
);
for
(
int
j
=
0
;
j
<
end
-
start
;
++
j
)
{
colArray
[
j
]
=
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
cols
[
j
+
start
]);
}
simd
::
batchAddTo
(
out
.
getRow
(
i
),
&
colArray
[
0
],
colNum
,
width
);
}
}
else
{
for
(
size_t
i
=
0
;
i
<
a
.
getHeight
();
++
i
)
{
const
int
start
=
a
.
getRowStartIdx
(
i
);
const
int
end
=
a
.
getRowStartIdx
(
i
+
1
);
for
(
int
j
=
start
;
j
<
end
;
++
j
)
{
vecAddTo
(
out
.
getRow
(
i
),
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
cols
[
j
]),
width
);
}
}
}
}
else
if
(
a
.
getValueType
()
==
FLOAT_VALUE
)
{
for
(
size_t
i
=
0
;
i
<
a
.
getHeight
();
++
i
)
{
const
int
start
=
a
.
getRowStartIdx
(
i
);
const
int
end
=
a
.
getRowStartIdx
(
i
+
1
);
for
(
int
j
=
start
;
j
<
end
;
++
j
)
{
vecAddTo
(
out
.
getRow
(
i
),
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
cols
[
j
]),
values
[
j
],
width
);
}
}
}
}
else
/*if (a->isTransposed())*/
{
size_t
m
=
a
.
getHeight
();
CHECK_EQ
(
b
.
getHeight
(),
m
);
CHECK_EQ
(
a
.
getWidth
(),
height
);
CHECK_EQ
(
b
.
getWidth
(),
width
);
if
(
a
.
getValueType
()
==
NO_VALUE
)
{
if
(
width
%
32
==
0
)
{
// use libaddto
CHECK_EQ
((
size_t
)
B
%
32
,
0UL
);
CHECK_EQ
((
size_t
)
C
%
32
,
0UL
);
for
(
size_t
i
=
0
;
i
<
a
.
getHeight
();
++
i
)
{
const
int
start
=
a
.
getRowStartIdx
(
i
);
const
int
end
=
a
.
getRowStartIdx
(
i
+
1
);
for
(
int
j
=
start
;
j
<
end
;
++
j
)
{
simd
::
addTo
(
out
.
getRow
(
cols
[
j
]),
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
i
),
width
);
}
}
}
else
{
for
(
size_t
i
=
0
;
i
<
a
.
getHeight
();
++
i
)
{
const
int
start
=
a
.
getRowStartIdx
(
i
);
const
int
end
=
a
.
getRowStartIdx
(
i
+
1
);
for
(
int
j
=
start
;
j
<
end
;
++
j
)
{
vecAddTo
(
out
.
getRow
(
cols
[
j
]),
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
i
),
width
);
}
}
}
}
else
if
(
a
.
getValueType
()
==
FLOAT_VALUE
)
{
for
(
size_t
i
=
0
;
i
<
a
.
getHeight
();
++
i
)
{
const
int
start
=
a
.
getRowStartIdx
(
i
);
const
int
end
=
a
.
getRowStartIdx
(
i
+
1
);
for
(
int
j
=
start
;
j
<
end
;
++
j
)
{
vecAddTo
(
out
.
getRow
(
cols
[
j
]),
const_cast
<
CpuMatrix
&>
(
b
).
getRow
(
i
),
values
[
j
],
width
);
}
}
}
}
}
}
}
}
...
...
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