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afa69024
编写于
10月 18, 2017
作者:
X
xzl
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add cuda and cpu pool_forward_with_mask impl
上级
96212132
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
260 addition
and
10 deletion
+260
-10
paddle/cuda/include/hl_cnn.h
paddle/cuda/include/hl_cnn.h
+41
-1
paddle/cuda/include/stub/hl_cnn_stub.h
paddle/cuda/include/stub/hl_cnn_stub.h
+18
-0
paddle/cuda/src/hl_cuda_cnn.cu
paddle/cuda/src/hl_cuda_cnn.cu
+55
-3
paddle/math/Matrix.cpp
paddle/math/Matrix.cpp
+93
-5
paddle/math/Matrix.h
paddle/math/Matrix.h
+53
-1
未找到文件。
paddle/cuda/include/hl_cnn.h
浏览文件 @
afa69024
...
@@ -18,7 +18,7 @@ limitations under the License. */
...
@@ -18,7 +18,7 @@ limitations under the License. */
#include "hl_base.h"
#include "hl_base.h"
/**
/**
* @brief Maximum pool forward.
* @brief Maximum pool forward
with Mask output
.
*
*
* @param[in] frameCnt batch size of input image.
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[in] inputData input data.
...
@@ -35,7 +35,47 @@ limitations under the License. */
...
@@ -35,7 +35,47 @@ limitations under the License. */
* @param[in] paddingW padding width.
* @param[in] paddingW padding width.
* @param[out] tgtData output data.
* @param[out] tgtData output data.
* @param[in] tgtStride stride between output data samples.
* @param[in] tgtStride stride between output data samples.
* @param[out] maskData the location indices of select max data
* @param[in] withMask set true if output maskData
*/
extern
void
hl_maxpool_forward
(
const
int
frameCnt
,
const
real
*
inputData
,
const
int
channels
,
const
int
height
,
const
int
width
,
const
int
pooledH
,
const
int
pooledW
,
const
int
sizeX
,
const
int
sizeY
,
const
int
strideH
,
const
int
strideW
,
const
int
paddingH
,
const
int
paddingW
,
real
*
tgtData
,
const
int
tgtStride
,
real
*
maskData
,
bool
withMask
);
/**
* @brief Maximum pool forward.
*
*
* @param[in] frameCnt batch size of input image.
* @param[in] inputData input data.
* @param[in] channels number of channel.
* @param[in] height image height.
* @param[in] width image width.
* @param[in] pooledH output image height.
* @param[in] pooledW output image width.
* @param[in] sizeX width of pooling window.
* @param[in] sizeY height of pooling window.
* @param[in] strideH pooling stride height.
* @param[in] strideW pooling stride width.
* @param[in] paddingH padding height.
* @param[in] paddingW padding width.
* @param[out] tgtData output data.
* @param[in] tgtStride stride between output data samples.
* @param[out] maskData the location indices of select max data
* @param[in] withMask set true if output maskData
*/
*/
extern
void
hl_maxpool_forward
(
const
int
frameCnt
,
extern
void
hl_maxpool_forward
(
const
int
frameCnt
,
const
real
*
inputData
,
const
real
*
inputData
,
...
...
paddle/cuda/include/stub/hl_cnn_stub.h
浏览文件 @
afa69024
...
@@ -33,6 +33,24 @@ inline void hl_maxpool_forward(const int frameCnt,
...
@@ -33,6 +33,24 @@ inline void hl_maxpool_forward(const int frameCnt,
real
*
tgtData
,
real
*
tgtData
,
const
int
tgtStride
)
{}
const
int
tgtStride
)
{}
inline
void
hl_maxpool_forward
(
const
int
frameCnt
,
const
real
*
inputData
,
const
int
channels
,
const
int
height
,
const
int
width
,
const
int
pooledH
,
const
int
pooledW
,
const
int
sizeX
,
const
int
sizeY
,
const
int
strideH
,
const
int
strideW
,
const
int
paddingH
,
const
int
paddingW
,
real
*
tgtData
,
const
int
tgtStride
,
real
*
MaskData
,
bool
withMask
)
{}
inline
void
hl_maxpool_backward
(
const
int
frameCnt
,
inline
void
hl_maxpool_backward
(
const
int
frameCnt
,
const
real
*
inputData
,
const
real
*
inputData
,
const
real
*
outData
,
const
real
*
outData
,
...
...
paddle/cuda/src/hl_cuda_cnn.cu
浏览文件 @
afa69024
...
@@ -31,7 +31,9 @@ __global__ void KeMaxPoolForward(const int nthreads,
...
@@ -31,7 +31,9 @@ __global__ void KeMaxPoolForward(const int nthreads,
const
int
offsetH
,
const
int
offsetH
,
const
int
offsetW
,
const
int
offsetW
,
real
*
tgtData
,
real
*
tgtData
,
const
int
tgtStride
)
{
const
int
tgtStride
,
real
*
maskData
,
bool
withMask
)
{
int
index
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
int
index
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
if
(
index
<
nthreads
)
{
if
(
index
<
nthreads
)
{
int
pw
=
index
%
pooledW
;
int
pw
=
index
%
pooledW
;
...
@@ -45,16 +47,22 @@ __global__ void KeMaxPoolForward(const int nthreads,
...
@@ -45,16 +47,22 @@ __global__ void KeMaxPoolForward(const int nthreads,
hstart
=
max
(
hstart
,
0
);
hstart
=
max
(
hstart
,
0
);
wstart
=
max
(
wstart
,
0
);
wstart
=
max
(
wstart
,
0
);
real
maxval
=
-
FLT_MAX
;
real
maxval
=
-
FLT_MAX
;
int
max_index
=
-
1
;
inputData
+=
(
frameNum
*
channels
+
c
)
*
height
*
width
;
inputData
+=
(
frameNum
*
channels
+
c
)
*
height
*
width
;
for
(
int
h
=
hstart
;
h
<
hend
;
++
h
)
{
for
(
int
h
=
hstart
;
h
<
hend
;
++
h
)
{
for
(
int
w
=
wstart
;
w
<
wend
;
++
w
)
{
for
(
int
w
=
wstart
;
w
<
wend
;
++
w
)
{
if
(
maxval
<
inputData
[
h
*
width
+
w
])
if
(
maxval
<
inputData
[
h
*
width
+
w
])
{
maxval
=
inputData
[
h
*
width
+
w
];
maxval
=
inputData
[
h
*
width
+
w
];
max_index
=
h
*
width
+
w
;
}
}
}
}
}
int
tgtIndex
=
int
tgtIndex
=
index
%
(
pooledW
*
pooledH
*
channels
)
+
frameNum
*
tgtStride
;
index
%
(
pooledW
*
pooledH
*
channels
)
+
frameNum
*
tgtStride
;
tgtData
[
tgtIndex
]
=
maxval
;
tgtData
[
tgtIndex
]
=
maxval
;
if
(
withMask
)
{
maskData
[
tgtIndex
]
=
max_index
;
}
}
}
}
}
...
@@ -92,7 +100,51 @@ void hl_maxpool_forward(const int frameCnt,
...
@@ -92,7 +100,51 @@ void hl_maxpool_forward(const int frameCnt,
paddingH
,
paddingH
,
paddingW
,
paddingW
,
tgtData
,
tgtData
,
tgtStride
);
tgtStride
,
NULL
,
false
);
CHECK_SYNC
(
"hl_maxpool_forward failed"
);
}
void
hl_maxpool_forward
(
const
int
frameCnt
,
const
real
*
inputData
,
const
int
channels
,
const
int
height
,
const
int
width
,
const
int
pooledH
,
const
int
pooledW
,
const
int
sizeX
,
const
int
sizeY
,
const
int
strideH
,
const
int
strideW
,
const
int
paddingH
,
const
int
paddingW
,
real
*
tgtData
,
const
int
tgtStride
,
real
*
maskData
,
bool
withMask
)
{
int
num_kernels
=
pooledH
*
pooledW
*
channels
*
frameCnt
;
int
blocks
=
(
num_kernels
+
1024
-
1
)
/
1024
;
dim3
threads
(
1024
,
1
);
dim3
grid
(
blocks
,
1
);
KeMaxPoolForward
<<<
grid
,
threads
,
0
,
STREAM_DEFAULT
>>>
(
num_kernels
,
inputData
,
channels
,
height
,
width
,
pooledH
,
pooledW
,
sizeX
,
sizeY
,
strideH
,
strideW
,
paddingH
,
paddingW
,
tgtData
,
tgtStride
,
maskData
,
withMask
);
CHECK_SYNC
(
"hl_maxpool_forward failed"
);
CHECK_SYNC
(
"hl_maxpool_forward failed"
);
}
}
...
...
paddle/math/Matrix.cpp
浏览文件 @
afa69024
...
@@ -1029,14 +1029,51 @@ void GpuMatrix::maxPoolForward(Matrix& inputMat,
...
@@ -1029,14 +1029,51 @@ void GpuMatrix::maxPoolForward(Matrix& inputMat,
size_t
outputW
,
size_t
outputW
,
size_t
paddingH
,
size_t
paddingH
,
size_t
paddingW
)
{
size_t
paddingW
)
{
maxPoolForward
(
inputMat
,
imgSizeH
,
imgSizeW
,
channels
,
sizeX
,
sizeY
,
strideH
,
strideW
,
outputH
,
outputW
,
paddingH
,
paddingW
,
NULL
,
false
);
}
void
GpuMatrix
::
maxPoolForward
(
Matrix
&
inputMat
,
size_t
imgSizeH
,
size_t
imgSizeW
,
size_t
channels
,
size_t
sizeX
,
size_t
sizeY
,
size_t
strideH
,
size_t
strideW
,
size_t
outputH
,
size_t
outputW
,
size_t
paddingH
,
size_t
paddingW
,
MatrixPtr
maskMatP
,
bool
withMask
)
{
CHECK
(
inputMat
.
useGpu_
==
true
)
<<
"Matrix type are not equal"
;
CHECK
(
inputMat
.
useGpu_
==
true
)
<<
"Matrix type are not equal"
;
real
*
inputData
=
inputMat
.
getData
();
real
*
inputData
=
inputMat
.
getData
();
real
*
maskData
=
NULL
;
size_t
frameNum
=
inputMat
.
getHeight
();
size_t
frameNum
=
inputMat
.
getHeight
();
CHECK
(
imgSizeH
*
imgSizeW
*
channels
==
inputMat
.
getWidth
());
CHECK
(
imgSizeH
*
imgSizeW
*
channels
==
inputMat
.
getWidth
());
CHECK
(
height_
==
inputMat
.
getHeight
());
CHECK
(
height_
==
inputMat
.
getHeight
());
CHECK
(
width_
==
outputH
*
outputW
*
channels
);
CHECK
(
width_
==
outputH
*
outputW
*
channels
);
if
(
withMask
)
{
CHECK
(
maskMatP
->
useGpu_
==
true
)
<<
"Matrix type are not equal"
;
CHECK
(
outputH
*
outputW
*
channels
==
maskMatP
->
getWidth
());
maskData
=
maskMatP
->
getData
();
}
hl_maxpool_forward
(
frameNum
,
hl_maxpool_forward
(
frameNum
,
inputData
,
inputData
,
channels
,
channels
,
...
@@ -1051,7 +1088,9 @@ void GpuMatrix::maxPoolForward(Matrix& inputMat,
...
@@ -1051,7 +1088,9 @@ void GpuMatrix::maxPoolForward(Matrix& inputMat,
paddingH
,
paddingH
,
paddingW
,
paddingW
,
data_
,
data_
,
getStride
());
getStride
(),
maskData
,
withMask
);
}
}
void
GpuMatrix
::
maxPoolBackward
(
Matrix
&
inputMat
,
void
GpuMatrix
::
maxPoolBackward
(
Matrix
&
inputMat
,
...
@@ -1974,8 +2013,39 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
...
@@ -1974,8 +2013,39 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
size_t
outputW
,
size_t
outputW
,
size_t
paddingH
,
size_t
paddingH
,
size_t
paddingW
)
{
size_t
paddingW
)
{
maxPoolForward
(
inputMat
,
imgSizeH
,
imgSizeW
,
channels
,
sizeX
,
sizeY
,
strideH
,
strideW
,
outputH
,
outputW
,
paddingH
,
paddingW
,
NULL
,
false
);
}
void
CpuMatrix
::
maxPoolForward
(
Matrix
&
inputMat
,
size_t
imgSizeH
,
size_t
imgSizeW
,
size_t
channels
,
size_t
sizeX
,
size_t
sizeY
,
size_t
strideH
,
size_t
strideW
,
size_t
outputH
,
size_t
outputW
,
size_t
paddingH
,
size_t
paddingW
,
MatrixPtr
maskMatP
,
bool
withMask
)
{
real
*
inputData
=
inputMat
.
getData
();
real
*
inputData
=
inputMat
.
getData
();
real
*
outData
=
data_
;
real
*
outData
=
data_
;
real
*
maskData
=
NULL
;
size_t
num
=
inputMat
.
getHeight
();
size_t
num
=
inputMat
.
getHeight
();
size_t
inLength
=
imgSizeH
*
imgSizeW
;
size_t
inLength
=
imgSizeH
*
imgSizeW
;
size_t
outLength
=
outputH
*
outputW
;
size_t
outLength
=
outputH
*
outputW
;
...
@@ -1984,6 +2054,11 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
...
@@ -1984,6 +2054,11 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
CHECK_EQ
(
channels
*
outLength
,
this
->
getWidth
());
CHECK_EQ
(
channels
*
outLength
,
this
->
getWidth
());
size_t
outStride
=
getStride
();
size_t
outStride
=
getStride
();
if
(
withMask
)
{
maskData
=
maskMatP
->
getData
();
CHECK_EQ
(
channels
*
outLength
,
maskMatP
->
getWidth
());
}
/* initialize the data_ */
/* initialize the data_ */
for
(
size_t
i
=
0
;
i
<
height_
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
height_
;
i
++
)
{
for
(
size_t
j
=
0
;
j
<
width_
;
j
++
)
{
for
(
size_t
j
=
0
;
j
<
width_
;
j
++
)
{
...
@@ -2005,10 +2080,21 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
...
@@ -2005,10 +2080,21 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
int
wstart
=
pw
*
strideW
-
paddingW
;
int
wstart
=
pw
*
strideW
-
paddingW
;
int
wend
=
std
::
min
(
wstart
+
sizeX
,
imgSizeW
);
int
wend
=
std
::
min
(
wstart
+
sizeX
,
imgSizeW
);
wstart
=
std
::
max
(
wstart
,
0
);
wstart
=
std
::
max
(
wstart
,
0
);
for
(
int
h
=
hstart
;
h
<
hend
;
++
h
)
{
if
(
!
withMask
)
{
for
(
int
w
=
wstart
;
w
<
wend
;
++
w
)
{
for
(
int
h
=
hstart
;
h
<
hend
;
++
h
)
{
outData
[
ph
*
outputW
+
pw
]
=
std
::
max
(
for
(
int
w
=
wstart
;
w
<
wend
;
++
w
)
{
outData
[
ph
*
outputW
+
pw
],
inputData
[
h
*
imgSizeW
+
w
]);
outData
[
ph
*
outputW
+
pw
]
=
std
::
max
(
outData
[
ph
*
outputW
+
pw
],
inputData
[
h
*
imgSizeW
+
w
]);
}
}
}
else
{
for
(
int
h
=
hstart
;
h
<
hend
;
++
h
)
{
for
(
int
w
=
wstart
;
w
<
wend
;
++
w
)
{
if
(
outData
[
ph
*
outputW
+
pw
]
<
inputData
[
h
*
imgSizeW
+
w
])
{
outData
[
ph
*
outputW
+
pw
]
=
inputData
[
h
*
imgSizeW
+
w
];
maskData
[
ph
*
outputW
+
pw
]
=
h
*
imgSizeW
+
w
;
}
}
}
}
}
}
}
}
...
@@ -2016,6 +2102,8 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
...
@@ -2016,6 +2102,8 @@ void CpuMatrix::maxPoolForward(Matrix& inputMat,
// compute offset
// compute offset
inputData
+=
inLength
;
inputData
+=
inLength
;
outData
+=
outLength
;
outData
+=
outLength
;
if
(
withMask
)
maskData
+=
outLength
;
}
}
}
}
}
}
...
...
paddle/math/Matrix.h
浏览文件 @
afa69024
...
@@ -861,7 +861,7 @@ public:
...
@@ -861,7 +861,7 @@ public:
/**
/**
* Pooling forward operation, pick out the largest element
* Pooling forward operation, pick out the largest element
* in the sizeX of value
* in the sizeX of value
.
*/
*/
virtual
void
maxPoolForward
(
Matrix
&
inputMat
,
virtual
void
maxPoolForward
(
Matrix
&
inputMat
,
size_t
imgSizeH
,
size_t
imgSizeH
,
...
@@ -878,6 +878,28 @@ public:
...
@@ -878,6 +878,28 @@ public:
LOG
(
FATAL
)
<<
"Not implemeted"
;
LOG
(
FATAL
)
<<
"Not implemeted"
;
}
}
/**
* Pooling forward operation, pick out the largest element
* in the sizeX of value, if set withMask true, it will
* also caculate the location indices.
*/
virtual
void
maxPoolForward
(
Matrix
&
inputMat
,
size_t
imgSizeH
,
size_t
imgSizeW
,
size_t
channels
,
size_t
sizeX
,
size_t
sizeY
,
size_t
strideH
,
size_t
strideW
,
size_t
outputH
,
size_t
outputW
,
size_t
paddingH
,
size_t
paddingW
,
MatrixPtr
maskMatP
,
bool
withMask
)
{
LOG
(
FATAL
)
<<
"Not implemeted"
;
}
/// Pooling backward operation.
/// Pooling backward operation.
virtual
void
maxPoolBackward
(
Matrix
&
image
,
virtual
void
maxPoolBackward
(
Matrix
&
image
,
size_t
imgSizeH
,
size_t
imgSizeH
,
...
@@ -1428,6 +1450,21 @@ public:
...
@@ -1428,6 +1450,21 @@ public:
size_t
paddingH
,
size_t
paddingH
,
size_t
paddingW
);
size_t
paddingW
);
void
maxPoolForward
(
Matrix
&
inputMat
,
size_t
imgSizeH
,
size_t
imgSizeW
,
size_t
channels
,
size_t
sizeX
,
size_t
sizeY
,
size_t
strideH
,
size_t
strideW
,
size_t
outputH
,
size_t
outputW
,
size_t
paddingH
,
size_t
paddingW
,
MatrixPtr
maskMatP
,
bool
withMask
);
void
maxPoolBackward
(
Matrix
&
image
,
void
maxPoolBackward
(
Matrix
&
image
,
size_t
imgSizeH
,
size_t
imgSizeH
,
size_t
imgSizeW
,
size_t
imgSizeW
,
...
@@ -1699,6 +1736,21 @@ public:
...
@@ -1699,6 +1736,21 @@ public:
size_t
paddingH
,
size_t
paddingH
,
size_t
paddingW
);
size_t
paddingW
);
void
maxPoolForward
(
Matrix
&
inputMat
,
size_t
imgSizeH
,
size_t
imgSizeW
,
size_t
channels
,
size_t
sizeX
,
size_t
sizeY
,
size_t
strideH
,
size_t
strideW
,
size_t
outputH
,
size_t
outputW
,
size_t
paddingH
,
size_t
paddingW
,
MatrixPtr
maskMatP
,
bool
withMask
);
void
maxPoolBackward
(
Matrix
&
image
,
void
maxPoolBackward
(
Matrix
&
image
,
size_t
imgSizeH
,
size_t
imgSizeH
,
size_t
imgSizeW
,
size_t
imgSizeW
,
...
...
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