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体验新版 GitCode,发现更多精彩内容 >>
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5edbe32f
编写于
1月 29, 2017
作者:
H
hedaoyuan
提交者:
GitHub
1月 29, 2017
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差异文件
Merge pull request #1216 from hedaoyuan/cmrnorm
Function Adds some properties
上级
db0df8f8
a9228e2a
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
111 addition
and
32 deletion
+111
-32
paddle/function/CrossMapNormalOp.cpp
paddle/function/CrossMapNormalOp.cpp
+82
-32
paddle/function/Function.h
paddle/function/Function.h
+29
-0
未找到文件。
paddle/function/CrossMapNormalOp.cpp
浏览文件 @
5edbe32f
...
...
@@ -162,38 +162,64 @@ template <DeviceType Device>
class
CrossMapNormalFunc
:
public
FunctionBase
{
public:
void
init
(
const
FuncConfig
&
config
)
override
{
// function arguments
size_
=
config
.
get
<
size_t
>
(
"size"
);
scale_
=
config
.
get
<
real
>
(
"scale"
);
pow_
=
config
.
get
<
real
>
(
"pow"
);
// number of inputs and outputs
numInputs_
=
1
;
numOutputs_
=
2
;
}
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
((
size_t
)
1
,
inputs
.
size
());
CHECK_EQ
((
size_t
)
2
,
outputs
.
size
());
CHECK_EQ
(
inputs
[
0
].
shape
().
ndims
(),
(
size_t
)
4
);
CHECK
(
inputs
[
0
].
shape
()
==
outputs
[
0
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
outputs
[
1
].
shape
());
check
(
inputs
,
outputs
);
// ArgType check still on here,
// not sure whether it is better to put inside the check.
CHECK_EQ
(
outputs
[
0
].
getArgType
(),
ASSIGN_TO
);
CHECK_EQ
(
outputs
[
1
].
getArgType
(),
ASSIGN_TO
);
size_t
samples
=
inputs
[
0
].
shape
()[
0
];
size_t
channel
s
=
inputs
[
0
].
shape
()[
1
];
size_t
height
=
inputs
[
0
].
shape
()[
2
];
size_t
width
=
inputs
[
0
].
shape
()[
3
];
size_t
batchSize
=
inputs
[
0
].
shape
()[
0
];
size_t
map
s
=
inputs
[
0
].
shape
()[
1
];
size_t
rows
=
inputs
[
0
].
shape
()[
2
];
size_t
columns
=
inputs
[
0
].
shape
()[
3
];
CrossMapNormal
<
Device
>
(
outputs
[
0
].
data
<
real
>
(),
outputs
[
1
].
data
<
real
>
(),
inputs
[
0
].
data
<
real
>
(),
samples
,
channel
s
,
height
,
width
,
batchSize
,
map
s
,
rows
,
columns
,
size_
,
scale_
,
pow_
);
}
void
check
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
(
numInputs_
,
inputs
.
size
());
CHECK_EQ
(
numOutputs_
,
outputs
.
size
());
CHECK_EQ
(
inputs
[
0
].
shape
().
ndims
(),
(
size_t
)
4
);
CHECK
(
inputs
[
0
].
shape
()
==
outputs
[
0
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
outputs
[
1
].
shape
());
}
// Only need the shape of the input, can calculate the
// floating-point operation.
size_t
ops
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
((
size_t
)
numInputs_
,
inputs
.
size
());
size_t
batchSize
=
inputs
[
0
].
shape
()[
0
];
size_t
maps
=
inputs
[
0
].
shape
()[
1
];
size_t
rows
=
inputs
[
0
].
shape
()[
2
];
size_t
columns
=
inputs
[
0
].
shape
()[
3
];
// number of floating-point operations
// an approximate value
size_t
ops
=
batchSize
*
maps
*
rows
*
columns
*
(
size_
*
2
+
3
);
return
ops
;
}
private:
size_t
size_
;
real
scale_
;
...
...
@@ -236,21 +262,18 @@ template <DeviceType Device>
class
CrossMapNormalGradFunc
:
public
FunctionBase
{
public:
void
init
(
const
FuncConfig
&
config
)
override
{
// function arguments
size_
=
config
.
get
<
size_t
>
(
"size"
);
scale_
=
config
.
get
<
real
>
(
"scale"
);
pow_
=
config
.
get
<
real
>
(
"pow"
);
// number of inputs and outputs
numInputs_
=
4
;
numOutputs_
=
1
;
}
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
((
size_t
)
4
,
inputs
.
size
());
CHECK_EQ
((
size_t
)
1
,
outputs
.
size
());
CHECK_EQ
(
inputs
[
0
].
shape
().
ndims
(),
(
size_t
)
4
);
CHECK
(
inputs
[
0
].
shape
()
==
inputs
[
1
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
inputs
[
2
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
inputs
[
3
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
outputs
[
0
].
shape
());
check
(
inputs
,
outputs
);
if
(
outputs
[
0
].
getArgType
()
!=
ADD_TO
)
{
// Currently, some algorithm implementations are ASSIGN_TO mode,
// if need to support the ADD_TO calculation, need to clear the output.
...
...
@@ -259,25 +282,52 @@ public:
tmp
.
zero
();
}
size_t
samples
=
inputs
[
0
].
shape
()[
0
];
size_t
channel
s
=
inputs
[
0
].
shape
()[
1
];
size_t
height
=
inputs
[
0
].
shape
()[
2
];
size_t
width
=
inputs
[
0
].
shape
()[
3
];
size_t
batchSize
=
inputs
[
0
].
shape
()[
0
];
size_t
map
s
=
inputs
[
0
].
shape
()[
1
];
size_t
rows
=
inputs
[
0
].
shape
()[
2
];
size_t
columns
=
inputs
[
0
].
shape
()[
3
];
CrossMapNormalGrad
<
Device
>
(
outputs
[
0
].
data
<
real
>
(),
inputs
[
0
].
data
<
real
>
(),
inputs
[
1
].
data
<
real
>
(),
inputs
[
2
].
data
<
real
>
(),
inputs
[
3
].
data
<
real
>
(),
samples
,
channel
s
,
height
,
width
,
batchSize
,
map
s
,
rows
,
columns
,
size_
,
scale_
,
pow_
);
}
void
check
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
(
numInputs_
,
inputs
.
size
());
CHECK_EQ
(
numOutputs_
,
outputs
.
size
());
CHECK_EQ
(
inputs
[
0
].
shape
().
ndims
(),
(
size_t
)
4
);
CHECK
(
inputs
[
0
].
shape
()
==
inputs
[
1
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
inputs
[
2
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
inputs
[
3
].
shape
());
CHECK
(
inputs
[
0
].
shape
()
==
outputs
[
0
].
shape
());
}
// Only need the shape of one input, can calculate the
// floating-point operation.
size_t
ops
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_LT
((
size_t
)
1
,
inputs
.
size
());
size_t
batchSize
=
inputs
[
0
].
shape
()[
0
];
size_t
maps
=
inputs
[
0
].
shape
()[
1
];
size_t
rows
=
inputs
[
0
].
shape
()[
2
];
size_t
columns
=
inputs
[
0
].
shape
()[
3
];
// number of floating-point operations
// an approximate value
size_t
ops
=
batchSize
*
maps
*
rows
*
columns
*
(
size_
*
4
+
2
);
return
ops
;
}
private:
size_t
size_
;
real
scale_
;
...
...
paddle/function/Function.h
浏览文件 @
5edbe32f
...
...
@@ -153,7 +153,36 @@ public:
virtual
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
{}
// This member function is used to check whether the BufferType and shape of
// the inputs and outputs arguments of the Function are correct.
// General calc function which will call this check to do arguments check.
// And before the calc called, the caller can also check their own arguments.
virtual
void
check
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
{}
// Calculate the number of floating-point operations of this Function.
// The inputs and outputs arguments do not need to contain the actual data,
// only the shape.
// And some Functions have the same input and output shapes,
// so you may not need to enter the complete number of arguments.
// But entering the full arguments is always correct for this interface.
virtual
size_t
ops
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
{
return
0
;
}
int
getNumInputs
()
const
{
return
numInputs_
;
}
int
getNumOutputs
()
const
{
return
numOutputs_
;
}
static
ClassRegistrar
<
FunctionBase
>
funcRegistrar_
;
protected:
// numInputs_ and numOutputs_ represents the maximum
// input and output supported by Function.
// Some functions are optimized for input and output,
// so when comparing the number of arguments, for these functions
// inputs.size() <= numInputs_ or outputs.size() <= numOutputs_
size_t
numInputs_
;
size_t
numOutputs_
;
};
#define FUNC_NAME(typeName, deviceName) #typeName "-" #deviceName
...
...
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