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52ceeedb
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52ceeedb
编写于
8月 13, 2017
作者:
C
chengduoZH
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add col2vol and vol2col CPU funtion
上级
23cf0c61
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
199 addition
and
0 deletion
+199
-0
paddle/math/Matrix.cpp
paddle/math/Matrix.cpp
+135
-0
paddle/math/Matrix.h
paddle/math/Matrix.h
+64
-0
未找到文件。
paddle/math/Matrix.cpp
浏览文件 @
52ceeedb
...
...
@@ -1389,6 +1389,52 @@ void GpuMatrix::multiBinaryLabelCrossEntropyBp(Matrix& output, Matrix& label) {
output_d
,
grad_d
,
mat_d
,
height_
,
width_
);
}
void
GpuMatrix
::
vol2Col
(
real
*
data
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
)
{
hl_matrix_vol2Col
(
data
,
channels
,
depth
,
height
,
width
,
filterD
,
filterH
,
filterW
,
strideD
,
strideH
,
strideW
,
paddingD
,
paddingH
,
paddingW
,
getData
());
}
void
GpuMatrix
::
col2Vol
(
real
*
trg
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
,
real
alpha
,
real
beta
)
{
hl_matrix_col2Vol
(
trg
,
channels
,
depth
,
height
,
width
,
filterD
,
filterH
,
filterW
,
strideD
,
strideH
,
strideW
,
paddingD
,
paddingH
,
paddingW
,
getData
(),
alpha
,
beta
);
}
/**
* CpuMatrix
*/
...
...
@@ -3975,6 +4021,95 @@ void CpuMatrix::bilinearBackward(const Matrix& out,
}
}
void
CpuMatrix
::
vol2Col
(
real
*
data
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
)
{
real
*
outData
=
getData
();
int
outHeight
=
(
height
+
2
*
paddingH
-
filterH
)
/
strideH
+
1
;
int
outWidth
=
(
width
+
2
*
paddingW
-
filterW
)
/
strideW
+
1
;
int
outDepth
=
(
depth
+
2
*
paddingD
-
filterD
)
/
strideD
+
1
;
int
channelsCol
=
channels
*
filterD
*
filterH
*
filterW
;
for
(
int
c
=
0
;
c
<
channelsCol
;
++
c
)
{
int
wOffset
=
c
%
filterW
;
int
hOffset
=
(
c
/
filterW
)
%
filterH
;
int
dOffset
=
(
c
/
filterW
/
filterH
)
%
filterD
;
int
cIn
=
c
/
filterW
/
filterH
/
filterD
;
for
(
int
d
=
0
;
d
<
outDepth
;
++
d
)
{
for
(
int
h
=
0
;
h
<
outHeight
;
++
h
)
{
for
(
int
w
=
0
;
w
<
outWidth
;
++
w
)
{
int
dPad
=
d
*
strideD
-
paddingD
+
dOffset
;
int
hPad
=
h
*
strideH
-
paddingH
+
hOffset
;
int
wPad
=
w
*
strideW
-
paddingW
+
wOffset
;
if
(
hPad
>=
0
&&
hPad
<
height
&&
wPad
>=
0
&&
wPad
<
width
&&
dPad
>=
0
&&
dPad
<
depth
)
outData
[((
c
*
outDepth
+
d
)
*
outHeight
+
h
)
*
outWidth
+
w
]
=
data
[((
cIn
*
depth
+
dPad
)
*
height
+
hPad
)
*
width
+
wPad
];
else
outData
[((
c
*
outDepth
+
d
)
*
outHeight
+
h
)
*
outWidth
+
w
]
=
0
;
}
}
}
}
}
void
CpuMatrix
::
col2Vol
(
real
*
trg
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
,
real
alpha
,
real
beta
)
{
real
*
src
=
getData
();
int
outDepth
=
(
depth
+
2
*
paddingH
-
filterD
)
/
strideD
+
1
;
int
outHeight
=
(
height
+
2
*
paddingH
-
filterH
)
/
strideH
+
1
;
int
outWidth
=
(
width
+
2
*
paddingW
-
filterW
)
/
strideW
+
1
;
int
channelsCol
=
channels
*
filterD
*
filterH
*
filterW
;
for
(
int
c
=
0
;
c
<
channelsCol
;
++
c
)
{
int
wOffset
=
c
%
filterW
;
int
hOffset
=
(
c
/
filterW
)
%
filterH
;
int
dOffset
=
(
c
/
filterW
/
filterH
)
%
filterD
;
int
cIm
=
c
/
filterW
/
filterH
/
filterD
;
for
(
int
d
=
0
;
d
<
outDepth
;
++
d
)
{
for
(
int
h
=
0
;
h
<
outHeight
;
++
h
)
{
for
(
int
w
=
0
;
w
<
outWidth
;
++
w
)
{
int
dPad
=
d
*
strideD
-
paddingD
+
dOffset
;
int
hPad
=
h
*
strideH
-
paddingH
+
hOffset
;
int
wPad
=
w
*
strideW
-
paddingW
+
wOffset
;
if
(
hPad
>=
0
&&
hPad
<
height
&&
wPad
>=
0
&&
wPad
<
width
&&
dPad
>=
0
&&
dPad
<
depth
)
trg
[((
cIm
*
depth
+
dPad
)
*
height
+
hPad
)
*
width
+
wPad
]
=
alpha
*
src
[((
c
*
outDepth
+
d
)
*
outHeight
+
h
)
*
outWidth
+
w
]
+
beta
*
trg
[((
cIm
*
depth
+
dPad
)
*
height
+
hPad
)
*
width
+
wPad
];
}
}
}
}
}
////////////////////////////////////////////////////////////////
// functions executed via cpu //
////////////////////////////////////////////////////////////////
...
...
paddle/math/Matrix.h
浏览文件 @
52ceeedb
...
...
@@ -1039,6 +1039,42 @@ public:
LOG
(
FATAL
)
<<
"Not implemented"
;
}
virtual
void
vol2Col
(
real
*
data
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
)
{
LOG
(
FATAL
)
<<
"Not implemeted"
;
}
virtual
void
col2Vol
(
real
*
trg
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
,
real
alpha
,
real
beta
)
{
LOG
(
FATAL
)
<<
"Not implemeted"
;
}
virtual
void
bilinearForward
(
const
Matrix
&
in
,
const
size_t
inImgH
,
const
size_t
inImgW
,
...
...
@@ -1374,6 +1410,20 @@ public:
const
real
ratioH
,
const
real
ratioW
);
void
vol2Col
(
real
*
data
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
);
void
col2Vol
(
real
*
trg
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
,
real
alpha
,
real
beta
);
void
multiBinaryLabelCrossEntropy
(
Matrix
&
output
,
Matrix
&
label
);
void
multiBinaryLabelCrossEntropyBp
(
Matrix
&
output
,
Matrix
&
label
);
...
...
@@ -1715,6 +1765,20 @@ public:
const
real
ratioH
,
const
real
ratioW
);
void
vol2Col
(
real
*
data
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
);
void
col2Vol
(
real
*
trg
,
int
channels
,
int
depth
,
int
height
,
int
width
,
int
filterD
,
int
filterH
,
int
filterW
,
int
strideD
,
int
strideH
,
int
strideW
,
int
paddingD
,
int
paddingH
,
int
paddingW
,
real
alpha
,
real
beta
);
template
<
typename
ExpressionType
>
void
operator
=
(
const
ExpressionType
&
expr
)
{
TensorCpuApply
<
real
>
(
*
this
,
expr
);
...
...
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