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体验新版 GitCode,发现更多精彩内容 >>
提交
d71396bf
编写于
9月 05, 2017
作者:
F
fengjiayi
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add global function `flatten_to_2d()`
上级
69fbc542
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
33 addition
and
34 deletion
+33
-34
paddle/framework/ddim.cc
paddle/framework/ddim.cc
+8
-6
paddle/framework/ddim.h
paddle/framework/ddim.h
+2
-2
paddle/framework/eigen.h
paddle/framework/eigen.h
+2
-5
paddle/framework/tensor_impl.h
paddle/framework/tensor_impl.h
+1
-5
paddle/operators/mul_op.cc
paddle/operators/mul_op.cc
+20
-16
未找到文件。
paddle/framework/ddim.cc
浏览文件 @
d71396bf
...
...
@@ -247,12 +247,6 @@ ssize_t product(const DDim& ddim) {
return
boost
::
apply_visitor
(
visitor
,
ddim
);
}
ssize_t
product
(
const
DDim
&
ddim
,
int
begin
,
int
end
)
{
ProductVisitor
visitor
;
DDim
sliced_ddim
=
slice_ddim
(
ddim
,
begin
,
end
);
return
boost
::
apply_visitor
(
visitor
,
sliced_ddim
);
}
/// \cond HIDDEN
struct
ArityVisitor
:
boost
::
static_visitor
<
int
>
{
...
...
@@ -289,5 +283,13 @@ std::ostream& operator<<(std::ostream& os, const DDim& ddim) {
DDim
::
DDim
(
std
::
initializer_list
<
int
>
init_list
)
{
*
this
=
make_ddim
(
init_list
);
}
DDim
flatten_to_2d
(
const
DDim
&
src
,
int
num_row_dims
)
{
int
rank
=
src
.
size
();
return
make_ddim
(
{
static_cast
<
int
>
(
product
(
slice_ddim
(
src
,
0
,
rank
-
num_row_dims
))),
static_cast
<
int
>
(
product
(
slice_ddim
(
src
,
rank
-
num_row_dims
,
rank
)))});
}
}
// namespace framework
}
// namespace paddle
paddle/framework/ddim.h
浏览文件 @
d71396bf
...
...
@@ -96,8 +96,6 @@ std::vector<int> vectorize(const DDim& ddim);
ssize_t
product
(
const
DDim
&
ddim
);
ssize_t
product
(
const
DDim
&
ddim
,
int
begin
,
int
end
);
/**
* \brief Slice a ddim
*
...
...
@@ -117,6 +115,8 @@ int arity(const DDim& ddim);
std
::
ostream
&
operator
<<
(
std
::
ostream
&
,
const
DDim
&
);
DDim
flatten_to_2d
(
const
DDim
&
src
,
int
num_row_dims
);
}
// namespace framework
}
// namespace paddle
...
...
paddle/framework/eigen.h
浏览文件 @
d71396bf
...
...
@@ -68,11 +68,8 @@ struct EigenMatrix : public EigenTensor<T, 2, MajorType, IndexType> {
int
rank
=
tensor
.
dims_
.
size
();
PADDLE_ENFORCE
(
num_row_dims
>
0
&&
num_row_dims
<
rank
,
"`num_row_dims` must be between (0, rank_of_tensor)."
);
return
EigenMatrix
::
From
(
tensor
,
make_ddim
({
static_cast
<
int
>
(
product
(
tensor
.
dims_
,
0
,
rank
-
num_row_dims
)),
static_cast
<
int
>
(
product
(
tensor
.
dims_
,
rank
-
num_row_dims
,
rank
))}));
return
EigenMatrix
::
From
(
tensor
,
flatten_to_2d
(
tensor
.
dims
(),
num_row_dims
));
}
};
...
...
paddle/framework/tensor_impl.h
浏览文件 @
d71396bf
...
...
@@ -152,11 +152,7 @@ template <typename T>
inline
Tensor
FlattenToMatrix
(
const
Tensor
&
src
,
int
num_row_dims
)
{
Tensor
res
;
res
.
ShareDataWith
<
T
>
(
src
);
DDim
src_dim
=
src
.
dims
();
int
rank
=
src_dim
.
size
();
res
.
Resize
(
make_ddim
(
{
static_cast
<
int
>
(
product
(
src_dim
,
0
,
rank
-
num_row_dims
)),
static_cast
<
int
>
(
product
(
src_dim
,
rank
-
num_row_dims
,
rank
))}));
res
.
Resize
(
flatten_to_2d
(
src
.
dims
(),
num_row_dims
));
return
res
;
}
...
...
paddle/operators/mul_op.cc
浏览文件 @
d71396bf
...
...
@@ -25,27 +25,27 @@ class MulOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
auto
x_dim
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
y_dim
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
auto
x_dim
s
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
y_dim
s
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
int
x_num_row_dims
=
GetAttr
<
int
>
(
"x_num_row_dims"
);
int
y_num_row_dims
=
GetAttr
<
int
>
(
"y_num_row_dims"
);
PADDLE_ENFORCE
(
x_dim
.
size
()
>
x_num_row_dims
,
PADDLE_ENFORCE
(
x_dim
s
.
size
()
>
x_num_row_dims
,
"The rank of input tensor X(%s) should be larger than "
"`mul_op`'s `x_num_row_dims`."
,
ctx
.
op
().
Input
(
"X"
));
PADDLE_ENFORCE
(
y_dim
.
size
()
>
y_num_row_dims
,
PADDLE_ENFORCE
(
y_dim
s
.
size
()
>
y_num_row_dims
,
"The rank of input tensor Y(%s) should be larger than "
"`mul_op`'s `y_num_row_dims`."
,
ctx
.
op
().
Input
(
"Y"
));
auto
x_mat_dims
=
framework
::
flatten_to_2d
(
x_dims
,
x_num_row_dims
);
auto
y_mat_dims
=
framework
::
flatten_to_2d
(
y_dims
,
y_num_row_dims
);
PADDLE_ENFORCE_EQ
(
product
(
x_dim
,
x_dim
.
size
()
-
x_num_row_dims
,
x_dim
.
size
()),
product
(
y_dim
,
0
,
y_dim
.
size
()
-
y_num_row_dims
),
x_mat_dims
[
1
],
y_mat_dims
[
0
],
"First matrix's width must be equal with second matrix's height."
);
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
(
{
static_cast
<
int
>
(
product
(
x_dim
,
0
,
x_dim
.
size
()
-
x_num_row_dims
)),
static_cast
<
int
>
(
product
(
y_dim
,
y_dim
.
size
()
-
y_num_row_dims
,
y_dim
.
size
()))});
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
({
x_mat_dims
[
0
],
y_mat_dims
[
1
]});
}
};
...
...
@@ -96,14 +96,18 @@ class MulOpGrad : public framework::OperatorWithKernel {
auto
out_dims
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
();
auto
*
x_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
y_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
PADDLE_ENFORCE
(
product
(
x_dims
,
0
,
x_dims
.
size
()
-
GetAttr
<
int
>
(
"x_num_row_dims"
))
==
out_dims
[
0
],
auto
x_mat_dims
=
framework
::
flatten_to_2d
(
x_dims
,
GetAttr
<
int
>
(
"x_num_row_dims"
));
auto
y_mat_dims
=
framework
::
flatten_to_2d
(
y_dims
,
GetAttr
<
int
>
(
"y_num_row_dims"
));
PADDLE_ENFORCE_EQ
(
x_mat_dims
[
0
],
out_dims
[
0
],
"The first dimension of Out@GRAD must equal to the first dimension of "
"the first operand."
);
PADDLE_ENFORCE
(
product
(
y_dims
,
y_dims
.
size
()
-
GetAttr
<
int
>
(
"y_num_row_dims"
),
y_dims
.
size
())
==
out_dims
[
1
],
PADDLE_ENFORCE_EQ
(
y_mat_dims
[
1
],
out_dims
[
1
],
"The second dimension of Out@GRAD must equal to the second "
"dimension of the second operand."
);
...
...
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