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体验新版 GitCode,发现更多精彩内容 >>
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0d9ba3da
编写于
11月 09, 2017
作者:
Y
yangyaming
浏览文件
操作
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电子邮件补丁
差异文件
Adapt to new interface.
上级
7be390aa
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
55 addition
and
56 deletion
+55
-56
paddle/operators/expand_op.cc
paddle/operators/expand_op.cc
+37
-32
paddle/operators/expand_op.h
paddle/operators/expand_op.h
+18
-24
未找到文件。
paddle/operators/expand_op.cc
浏览文件 @
0d9ba3da
...
...
@@ -24,26 +24,28 @@ class ExpandOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"X"
),
"X must be initialized."
);
std
::
vector
<
int
>
expand_times
=
Attr
<
std
::
vector
<
int
>>
(
"expandTimes"
);
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
PADDLE_ENFORCE_EQ
(
x_dims
.
size
(),
expand_times
.
size
(),
"The number of expandTimes's value must be equal "
"to the rank of X."
);
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) must be initialized."
);
std
::
vector
<
int
>
expand_times
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"expandTimes"
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE_EQ
(
static_cast
<
size_t
>
(
x_dims
.
size
()),
expand_times
.
size
(),
"The number of Attr(expandTimes)'s value must be equal "
"to the rank of Input(X)."
);
PADDLE_ENFORCE_LE
(
x_dims
.
size
(),
6
,
"The rank of
X
must not be greater than 6."
);
"The rank of
Input(X)
must not be greater than 6."
);
std
::
vector
<
int64_t
>
out_shape
(
x_dims
.
size
());
for
(
size_t
i
=
0
;
i
<
expand_times
.
size
();
++
i
)
{
PADDLE_ENFORCE_GE
(
expand_times
[
i
],
1
,
"Each value of
expandTimes
should not be "
"Each value of
Attr(expandTimes)
should not be "
"less than 1."
);
out_shape
[
i
]
=
x_dims
[
i
]
*
expand_times
[
i
];
}
auto
*
out
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
out
->
Resize
(
framework
::
make_ddim
(
out_shape
));
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
out_shape
));
ctx
->
ShareLoD
(
"X"
,
"Out"
);
}
};
...
...
@@ -52,20 +54,21 @@ class ExpandOpMaker : public framework::OpProtoAndCheckerMaker {
ExpandOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"
The input tensor of expand op
."
"
The rank of X should be between in 1 and 6
."
);
"
(Tensor, default Tensor<float>) A tensor with rank in [1, 6]
."
"
X is the input tensor to be expanded
."
);
AddOutput
(
"Out"
,
"Output tensor of expand op."
"The rank of Out is same as X except that each dimension size "
"of Out equals to corresponding dimension size of X multiplying "
"corresponding value of expandTimes."
);
"(Tensor, default Tensor<float>) A tensor with rank in [1, 6]."
"The rank of Output(Out) is same as Input(X) except that each "
"dimension size of Output(Out) is equal to corresponding "
"dimension size of Input(X) multiplying corresponding value of "
"Attr(expandTimes)."
);
AddAttr
<
std
::
vector
<
int
>>
(
"expandTimes"
,
"Expand times number for each dimension."
);
AddComment
(
R"DOC(
Expand operator tiles the input by given times number. You should set times
number for each dimension by providing attribute 'expandTimes'. The rank of X
should be
between in 1 and 6. Please notice that size of 'expandTimes' must be
same with
X's rank.
should be
in [1, 6]. Please notice that size of 'expandTimes' must be same with
X's rank.
)DOC"
);
}
};
...
...
@@ -75,25 +78,27 @@ class ExpandGradOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"X"
),
"X must be initialized."
);
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null."
);
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
std
::
vector
<
int
>
expand_times
=
Attr
<
std
::
vector
<
int
>>
(
"expandTimes"
);
auto
out_dims
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
();
auto
*
x_grad
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"X"
));
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null."
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
std
::
vector
<
int
>
expand_times
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"expandTimes"
);
auto
out_dims
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
for
(
size_t
i
=
0
;
i
<
expand_times
.
size
();
++
i
)
{
PADDLE_ENFORCE_EQ
(
x_dims
[
i
]
*
expand_times
[
i
],
out_dims
[
i
],
"Each dimension size of Input(Out@GRAD) should be "
"equal to multiplication of crroresponding dimension "
"size of Input(X) and
expandTimes
value."
);
"size of Input(X) and
Attr(expandTimes)
value."
);
}
if
(
x_grad
)
x_grad
->
Resize
(
x_dims
);
auto
x_grad_name
=
framework
::
GradVarName
(
"X"
);
if
(
ctx
->
HasOutput
(
x_grad_name
))
{
ctx
->
SetOutputDim
(
x_grad_name
,
x_dims
);
}
}
};
...
...
paddle/operators/expand_op.h
浏览文件 @
0d9ba3da
...
...
@@ -45,6 +45,8 @@
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenVector
=
framework
::
EigenVector
<
T
,
MajorType
,
IndexType
>
;
...
...
@@ -53,24 +55,24 @@ template <typename T, size_t D, int MajorType = Eigen::RowMajor,
using
EigenTensor
=
framework
::
EigenTensor
<
T
,
D
,
MajorType
,
IndexType
>
;
template
<
typename
Place
,
typename
T
>
class
ExpandKernel
:
public
framework
::
OpKernel
{
class
ExpandKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
rank
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
)
->
dims
().
size
();
auto
rank
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
switch
(
rank
)
{
REP_EXPAND_TEMPLATE
(
6
)
default:
PADDLE_ENFORCE
(
false
,
"Only support tensor with rank being between 1 and 6."
);
}
;
}
}
protected:
template
<
int
Rank
>
void
Expand
(
const
framework
::
ExecutionContext
&
context
)
const
{
auto
*
in0
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
in0
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
&
expand_times
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"expandTimes"
);
auto
*
out0
=
context
.
Output
<
framework
::
LoD
Tensor
>
(
"Out"
);
auto
*
out0
=
context
.
Output
<
Tensor
>
(
"Out"
);
Eigen
::
DSizes
<
int
,
Rank
>
bcast_dims
;
auto
x_dims
=
in0
->
dims
();
for
(
size_t
i
=
0
;
i
<
expand_times
.
size
();
++
i
)
{
...
...
@@ -85,10 +87,10 @@ class ExpandKernel : public framework::OpKernel {
};
template
<
typename
Place
,
typename
T
>
class
ExpandGradKernel
:
public
framework
::
OpKernel
{
class
ExpandGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
in0
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
*
in0
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
&
expand_times
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"expandTimes"
);
auto
x_dims
=
in0
->
dims
();
std
::
vector
<
int
>
reshape_dims_vec
;
...
...
@@ -111,23 +113,17 @@ class ExpandGradKernel : public framework::OpKernel {
int
dims
=
reshape_dims_vec
.
size
()
*
6
+
reduce_dims_vec
.
size
()
-
7
;
// no need reduce, just copy
if
(
reduce_dims_vec
.
size
()
==
0
)
{
auto
*
in0
=
context
.
Input
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
out0
=
context
.
Output
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
in0
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
out0
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
out0
->
mutable_data
<
T
>
(
context
.
GetPlace
());
if
(
platform
::
is_cpu_place
(
context
.
GetPlace
()))
{
out0
->
CopyFrom
<
T
>
(
*
in0
,
platform
::
CPUPlace
());
}
else
{
out0
->
CopyFrom
<
T
>
(
*
in0
,
platform
::
GPUPlace
());
}
out0
->
CopyFrom
(
*
in0
,
context
.
GetPlace
(),
context
.
device_context
());
}
else
{
switch
(
dims
)
{
REP_EXPAND_GRAD_TEMPLATE
(
72
)
default:
PADDLE_ENFORCE
(
false
,
"Only support tensor with rank being between 1 and 6."
);
}
;
}
}
}
...
...
@@ -144,11 +140,9 @@ class ExpandGradKernel : public framework::OpKernel {
PADDLE_ENFORCE_EQ
(
reduce_size
,
reduce_dims_vec
.
size
(),
"Inconsistent size between template Dims and "
"reduce dimensions."
);
auto
*
in0
=
context
.
Input
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
out0
=
context
.
Output
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"X"
));
auto
x
=
EigenVector
<
T
>::
Flatten
(
*
(
context
.
Input
<
framework
::
Tensor
>
(
"X"
)));
auto
*
in0
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
out0
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
x
=
EigenVector
<
T
>::
Flatten
(
*
(
context
.
Input
<
Tensor
>
(
"X"
)));
out0
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
x_grad
=
EigenVector
<
T
>::
Flatten
(
*
out0
);
Eigen
::
DSizes
<
int
,
Dims
/
6
+
1
>
reshape_dims
;
...
...
@@ -165,5 +159,5 @@ class ExpandGradKernel : public framework::OpKernel {
}
};
}
// operators
}
// paddle
}
//
namespace
operators
}
//
namespace
paddle
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