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f31217fc
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体验新版 GitCode,发现更多精彩内容 >>
提交
f31217fc
编写于
9月 11, 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 issues
上级
ba8a5c15
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
14 addition
and
12 deletion
+14
-12
paddle/operators/pad_op.cc
paddle/operators/pad_op.cc
+3
-2
paddle/operators/pad_op.h
paddle/operators/pad_op.h
+11
-10
未找到文件。
paddle/operators/pad_op.cc
浏览文件 @
f31217fc
...
...
@@ -27,10 +27,10 @@ class PadOp : public framework::OperatorWithKernel {
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
auto
x_dim
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
paddings
=
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
PADDLE_ENFORCE_EQ
(
x_dim
.
size
()
*
2
,
int
(
paddings
.
size
()),
PADDLE_ENFORCE_EQ
(
x_dim
.
size
()
*
2
,
int
64_t
(
paddings
.
size
()),
"Size of paddings should be equal to 2 * dimension size "
"of input tensor."
);
std
::
vector
<
int
>
out_dims
(
x_dim
.
size
());
std
::
vector
<
int
64_t
>
out_dims
(
x_dim
.
size
());
for
(
int
i
=
0
;
i
<
x_dim
.
size
();
++
i
)
{
out_dims
[
i
]
=
x_dim
[
i
]
+
paddings
[
i
*
2
]
+
paddings
[
i
*
2
+
1
];
}
...
...
@@ -95,6 +95,7 @@ class PadOpGrad : public framework::OperatorWithKernel {
"Input(Out@GRAD) should not be null"
);
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
*
x_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
PADDLE_ENFORCE_NOT_NULL
(
x_grad
,
"Output(X@GRAD) should not be null"
);
x_grad
->
Resize
(
x_dims
);
}
...
...
paddle/operators/pad_op.h
浏览文件 @
f31217fc
...
...
@@ -28,18 +28,17 @@ using EigenTensor = framework::EigenTensor<T, D, MajorType, IndexType>;
template
<
typename
Place
,
typename
T
,
size_t
D
>
void
PadFunction
(
const
framework
::
ExecutionContext
&
context
)
{
auto
pads
=
context
.
Get
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
auto
pads
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
int
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
paddings
[
i
].
first
=
pads
[
i
*
2
];
paddings
[
i
].
second
=
pads
[
i
*
2
+
1
];
}
T
pad_value
=
context
.
Get
Attr
<
T
>
(
"pad_value"
);
T
pad_value
=
context
.
Attr
<
T
>
(
"pad_value"
);
auto
*
x
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
*
out
=
context
.
Output
<
Tensor
>
(
"Out"
);
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dims
=
x
->
dims
();
auto
x_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
x
);
auto
out_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
out
);
...
...
@@ -51,8 +50,8 @@ template <typename Place, typename T>
class
PadKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
int
dim
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
switch
(
dim
)
{
int
rank
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
switch
(
rank
)
{
case
1
:
PadFunction
<
Place
,
T
,
1
>
(
context
);
break
;
...
...
@@ -72,14 +71,15 @@ class PadKernel : public framework::OpKernel {
PadFunction
<
Place
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"Only ranks up to 6 supported."
);
PADDLE_THROW
(
"PadOp only support tensors with no more than 6 dimensions."
);
}
}
};
template
<
typename
Place
,
typename
T
,
size_t
D
>
void
PadGradFunction
(
const
framework
::
ExecutionContext
&
context
)
{
auto
pads
=
context
.
Get
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
auto
pads
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
int
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
paddings
[
i
].
first
=
-
pads
[
i
*
2
];
...
...
@@ -99,9 +99,9 @@ template <typename Place, typename T>
class
PadGradKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
size_t
dim
=
size_t
rank
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
().
size
();
switch
(
dim
)
{
switch
(
rank
)
{
case
1
:
PadGradFunction
<
Place
,
T
,
1
>
(
context
);
break
;
...
...
@@ -121,7 +121,8 @@ class PadGradKernel : public framework::OpKernel {
PadGradFunction
<
Place
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"Only ranks up to 6 supported."
);
PADDLE_THROW
(
"PadOp only support tensors with no more than 6 dimensions."
);
}
}
};
...
...
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