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3ce974b9
编写于
5月 31, 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 group argument in ConvFunctionBase
上级
048b14a9
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
49 addition
and
34 deletion
+49
-34
paddle/function/ConvOp.h
paddle/function/ConvOp.h
+6
-0
paddle/function/ConvOpTest.cpp
paddle/function/ConvOpTest.cpp
+1
-0
paddle/function/GemmConvOp.cpp
paddle/function/GemmConvOp.cpp
+42
-34
未找到文件。
paddle/function/ConvOp.h
浏览文件 @
3ce974b9
...
@@ -38,6 +38,7 @@ public:
...
@@ -38,6 +38,7 @@ public:
// function arguments
// function arguments
strides_
=
config
.
get
<
std
::
vector
<
size_t
>>
(
"strides"
);
strides_
=
config
.
get
<
std
::
vector
<
size_t
>>
(
"strides"
);
paddings_
=
config
.
get
<
std
::
vector
<
size_t
>>
(
"paddings"
);
paddings_
=
config
.
get
<
std
::
vector
<
size_t
>>
(
"paddings"
);
groups_
=
config
.
get
<
size_t
>
(
"groups"
);
// number of inputs and outputs
// number of inputs and outputs
numInputs_
=
2
;
numInputs_
=
2
;
...
@@ -62,6 +63,11 @@ public:
...
@@ -62,6 +63,11 @@ public:
protected:
protected:
std
::
vector
<
size_t
>
strides_
;
std
::
vector
<
size_t
>
strides_
;
std
::
vector
<
size_t
>
paddings_
;
std
::
vector
<
size_t
>
paddings_
;
/// Group size, refer to grouped convolution in
/// Alex Krizhevsky's paper: when group=2, the first half of the
/// filters are only connected to the first half of the input channels,
/// and the second half only connected to the second half.
size_t
groups_
;
inline
int
strideH
()
const
{
return
strides_
[
0
];
}
inline
int
strideH
()
const
{
return
strides_
[
0
];
}
inline
int
strideW
()
const
{
return
strides_
[
1
];
}
inline
int
strideW
()
const
{
return
strides_
[
1
];
}
...
...
paddle/function/ConvOpTest.cpp
浏览文件 @
3ce974b9
...
@@ -55,6 +55,7 @@ public:
...
@@ -55,6 +55,7 @@ public:
FuncConfig
()
FuncConfig
()
.
set
(
"paddings"
,
paddings
)
.
set
(
"paddings"
,
paddings
)
.
set
(
"strides"
,
strides
)
.
set
(
"strides"
,
strides
)
.
set
(
"groups"
,
(
size_t
)
1
)
.
set
(
"algo"
,
algo
));
.
set
(
"algo"
,
algo
));
TensorShape
shape0
{
TensorShape
shape0
{
...
...
paddle/function/GemmConvOp.cpp
浏览文件 @
3ce974b9
...
@@ -101,49 +101,57 @@ public:
...
@@ -101,49 +101,57 @@ public:
size_t
outputHeight
=
outputs
[
0
].
shape
()[
2
];
size_t
outputHeight
=
outputs
[
0
].
shape
()[
2
];
size_t
outputWidth
=
outputs
[
0
].
shape
()[
3
];
size_t
outputWidth
=
outputs
[
0
].
shape
()[
3
];
CHECK_EQ
(
inputChannels
/
groups_
,
inputs
[
1
].
shape
()[
1
]);
real
*
inputData
=
inputs
[
0
].
data
<
real
>
();
real
*
inputData
=
inputs
[
0
].
data
<
real
>
();
real
*
filterData
=
inputs
[
1
].
data
<
real
>
();
real
*
filterData
=
inputs
[
1
].
data
<
real
>
();
real
*
outputData
=
outputs
[
0
].
data
<
real
>
();
real
*
outputData
=
outputs
[
0
].
data
<
real
>
();
size_t
size
=
size_t
size
=
inputChannels
/
groups_
*
filterHeight
*
filterWidth
*
inputChannels
*
filterHeight
*
filterWidth
*
outputHeight
*
outputWidth
;
outputHeight
*
outputWidth
;
resizeBuffer
(
size
);
resizeBuffer
(
size
);
real
*
colData
=
reinterpret_cast
<
real
*>
(
memory_
->
getBuf
());
real
*
colData
=
reinterpret_cast
<
real
*>
(
memory_
->
getBuf
());
Im2ColFunctor
<
real
>
im2col
;
Im2ColFunctor
<
real
>
im2col
;
size_t
inputOffset
=
(
inputChannels
/
groups_
)
*
inputHeight
*
inputWidth
;
size_t
outputOffset
=
(
outputChannels
/
groups_
)
*
outputHeight
*
outputWidth
;
size_t
filterOffset
=
inputs
[
1
].
shape
().
getElements
()
/
groups_
;
for
(
size_t
i
=
0
;
i
<
batchSize
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
batchSize
;
i
++
)
{
im2col
(
inputData
,
for
(
int
g
=
0
;
g
<
groups_
;
g
++
)
{
inputChannels
,
im2col
(
inputData
+
g
*
inputOffset
,
inputHeight
,
inputChannels
/
groups_
,
inputWidth
,
inputHeight
,
filterHeight
,
inputWidth
,
filterWidth
,
filterHeight
,
strideH
(),
filterWidth
,
strideW
(),
strideH
(),
paddingH
(),
strideW
(),
paddingW
(),
paddingH
(),
outputHeight
,
paddingW
(),
outputWidth
,
outputHeight
,
colData
);
outputWidth
,
colData
);
int
M
=
outputChannels
;
int
N
=
outputHeight
*
outputWidth
;
int
M
=
outputChannels
;
int
K
=
inputChannels
*
filterHeight
*
filterWidth
;
int
N
=
outputHeight
*
outputWidth
;
gemm
<
real
>
(
CblasNoTrans
,
int
K
=
inputChannels
*
filterHeight
*
filterWidth
;
CblasNoTrans
,
gemm
<
real
>
(
CblasNoTrans
,
M
,
CblasNoTrans
,
N
,
M
,
K
,
N
,
1.0
f
,
K
,
filterData
,
1.0
f
,
K
,
filterData
+
g
*
filterOffset
,
colData
,
K
,
N
,
colData
,
0.0
f
,
N
,
outputData
,
0.0
f
,
N
);
outputData
+
g
*
outputOffset
,
inputData
+=
inputChannels
*
inputHeight
*
inputWidth
;
N
);
outputData
+=
outputChannels
*
outputHeight
*
outputWidth
;
inputData
+=
inputChannels
*
inputHeight
*
inputWidth
;
outputData
+=
outputChannels
*
outputHeight
*
outputWidth
;
}
}
}
}
}
...
...
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