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3eadb42d
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3eadb42d
编写于
9月 06, 2017
作者:
W
wanghaoshuang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Fix eigen error.
上级
2db7dede
变更
3
显示空白变更内容
内联
并排
Showing
3 changed file
with
101 addition
and
44 deletion
+101
-44
paddle/operators/pad_op.cc
paddle/operators/pad_op.cc
+6
-6
paddle/operators/pad_op.h
paddle/operators/pad_op.h
+85
-35
python/paddle/v2/framework/tests/test_pad_op.py
python/paddle/v2/framework/tests/test_pad_op.py
+10
-3
未找到文件。
paddle/operators/pad_op.cc
浏览文件 @
3eadb42d
...
...
@@ -26,18 +26,18 @@ class PadOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
auto
dim0
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
dim1
=
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
dims
(
);
auto
paddings
=
GetAttr
<
std
::
vector
<
std
::
pair
<
int32
,
int32
>>>
(
"paddings"
);
auto
paddings
=
GetAttr
<
std
::
vector
<
std
::
pair
<
int
,
int
>>>
(
"paddings"
);
std
::
vector
<
int
>
dim1
(
dim0
.
size
()
);
for
(
int
i
=
0
;
i
<
dim0
.
size
();
++
i
)
{
dim1
[
i
]
=
dim0
[
i
]
+
paddings
[
i
]
[
0
]
+
paddings
[
i
][
1
]
;
dim1
[
i
]
=
dim0
[
i
]
+
paddings
[
i
]
.
first
+
paddings
[
i
].
second
;
}
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
(
dim1
);
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
(
paddle
::
framework
::
make_ddim
(
dim1
)
);
}
};
class
Mul
OpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
class
Pad
OpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
Mul
OpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
Pad
OpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The input of pad op"
);
AddOutput
(
"Out"
,
"The output of pad op"
);
...
...
paddle/operators/pad_op.h
浏览文件 @
3eadb42d
...
...
@@ -28,12 +28,13 @@ template <typename T, size_t D, int MajorType = Eigen::RowMajor,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenTensor
=
framework
::
EigenTensor
<
T
,
D
,
MajorType
,
IndexType
>
;
template
<
typename
Place
,
typename
T
>
class
PadKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
paddings
=
context
.
op_
.
GetAttr
<
std
::
vector
<
std
::
pair
<
int
,
int
>>>
(
"paddings"
);
template
<
typename
Place
,
typename
T
,
size_t
D
>
void
PadFunction
(
const
framework
::
ExecutionContext
&
context
)
{
auto
pads
=
context
.
op_
.
GetAttr
<
std
::
vector
<
std
::
pair
<
int
,
int
>>>
(
"paddings"
);
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
int
i
=
0
;
i
<
pads
.
size
();
++
i
)
{
paddings
[
i
]
=
pads
[
i
];
}
T
pad_value
=
context
.
op_
.
GetAttr
<
T
>
(
"pad_value"
);
auto
*
X
=
context
.
Input
<
Tensor
>
(
"X"
);
...
...
@@ -41,39 +42,88 @@ class PadKernel : public framework::OpKernel {
Out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dims
=
X
->
dims
();
// Eigen::TensorMap<Eigen::Tensor<const T, 2, Eigen::RowMajor,
// Eigen::DenseIndex>> X_tensor = EigenTensor<T, 2>::From(*X);
// Eigen::TensorMap<Eigen::Tensor<T, 2, Eigen::RowMajor, Eigen::DenseIndex>>
// Out_tensor = EigenTensor<T, 2>::From(*Out);
EigenTensor
<
T
,
dims
.
size
()
>::
ConstType
X_tensor
=
EigenTensor
<
T
,
dims
.
size
()
>::
From
(
*
X
);
EigenTensor
<
T
,
dims
.
size
()
>::
Type
Out_tensor
=
EigenTensor
<
T
,
dims
.
size
()
>::
From
(
*
Out
);
Out_tensor
=
X_tensor
.
pad
(
paddings
,
pad_value
);
}
};
auto
X_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
X
);
auto
Out_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
Out
);
auto
place
=
context
.
GetEigenDevice
<
Place
>
();
Out_tensor
.
device
(
place
)
=
X_tensor
.
pad
(
paddings
,
pad_value
);
}
template
<
typename
Place
,
typename
T
>
class
Pad
Grad
Kernel
:
public
framework
::
OpKernel
{
class
PadKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
std
::
vector
<
std
::
pair
<
int
,
int
>>
paddings
=
context
.
op_
.
GetAttr
<
std
::
vector
<
std
::
pair
<
int
,
int
>>>
(
"paddings"
);
for
(
int
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
int
dim
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
switch
(
dim
)
{
case
1
:
PadFunction
<
Place
,
T
,
1
>
(
context
);
break
;
case
2
:
PadFunction
<
Place
,
T
,
2
>
(
context
);
break
;
case
3
:
PadFunction
<
Place
,
T
,
3
>
(
context
);
break
;
case
4
:
PadFunction
<
Place
,
T
,
4
>
(
context
);
break
;
case
5
:
PadFunction
<
Place
,
T
,
5
>
(
context
);
break
;
case
6
:
PadFunction
<
Place
,
T
,
6
>
(
context
);
break
;
default:
LOG
(
ERROR
)
<<
"Only ranks up to 6 supported."
;
}
}
};
template
<
typename
Place
,
typename
T
,
size_t
D
>
void
PadGradFunction
(
const
framework
::
ExecutionContext
&
context
)
{
auto
pads
=
context
.
op_
.
GetAttr
<
std
::
vector
<
std
::
pair
<
int
,
int
>>>
(
"paddings"
);
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
int
i
=
0
;
i
<
pads
.
size
();
++
i
)
{
paddings
[
0
].
first
=
-
paddings
[
0
].
first
;
paddings
[
1
].
second
=
-
paddings
[
1
].
second
;
}
auto
*
dOut
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
dims
=
dOut
->
dims
();
auto
*
dOut
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
dX
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
dX
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
*
dX
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
dX
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
dX_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
dX
);
auto
dOut_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
dOut
);
auto
place
=
context
.
GetEigenDevice
<
Place
>
();
dX_tensor
.
device
(
place
)
=
dOut_tensor
.
pad
(
paddings
,
0
);
}
EigenTensor
<
T
,
dims
.
size
()
>::
Type
dX_tensor
=
EigenTensor
<
T
,
dims
.
size
()
>::
From
(
*
dX
);
EigenTensor
<
T
,
dims
.
size
()
>::
ConstType
dOut_tensor
=
EigenTensor
<
T
,
dims
.
size
()
>::
From
(
*
dOut
);
dX_tensor
=
dOut_tensor
.
pad
(
paddings
,
0
);
template
<
typename
Place
,
typename
T
>
class
PadGradKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
size_t
dim
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
().
size
();
switch
(
dim
)
{
case
1
:
PadGradFunction
<
Place
,
T
,
1
>
(
context
);
break
;
case
2
:
PadGradFunction
<
Place
,
T
,
2
>
(
context
);
break
;
case
3
:
PadGradFunction
<
Place
,
T
,
3
>
(
context
);
break
;
case
4
:
PadGradFunction
<
Place
,
T
,
4
>
(
context
);
break
;
case
5
:
PadGradFunction
<
Place
,
T
,
5
>
(
context
);
break
;
case
6
:
PadGradFunction
<
Place
,
T
,
6
>
(
context
);
break
;
default:
LOG
(
ERROR
)
<<
"Only ranks up to 6 supported."
;
}
}
};
...
...
python/paddle/v2/framework/tests/test_pad_op.py
浏览文件 @
3eadb42d
import
unittest
import
numpy
as
np
from
paddle.v2.framework.op
import
Operator
from
gradient_checker
import
GradientChecker
,
create_op
from
op_test_util
import
OpTestMeta
...
...
@@ -10,19 +11,25 @@ class TestPadOp(unittest.TestCase):
def
setUp
(
self
):
self
.
type
=
"pad"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
((
16
,
16
)).
astype
(
"float32"
),
}
self
.
attrs
[
'paddings'
]
=
((
0
,
1
),
(
2
,
3
))
self
.
attrs
=
{}
self
.
attrs
[
'paddings'
]
=
[(
0
,
1
),
(
2
,
3
)]
self
.
attrs
[
'pad_value'
]
=
0
self
.
outputs
=
{
'Out'
:
np
.
pad
(
self
.
inputs
[
'X'
],
self
.
attrs
[
'paddings'
],
mode
=
'constant'
,
constant_value
=
0
)
constant_value
s
=
0
)
}
class
PadGradOpTest
(
GradientChecker
):
def
test_pad
(
self
):
op
=
Operator
(
"pad"
,
paddings
=
((
0
,
1
),
(
2
,
3
)),
pad_value
=
0
)
op
=
Operator
(
type
=
"pad"
,
X
=
"X"
,
Out
=
"Out"
,
paddings
=
[(
0
,
1
),
(
2
,
3
)],
pad_value
=
0
)
inputs
=
{
'X'
:
np
.
random
.
random
((
16
,
16
)).
astype
(
"float32"
),
}
self
.
check_grad
(
op
,
inputs
,
set
([
"X"
]),
"Out"
,
max_relative_error
=
0.5
)
...
...
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