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9c3739b0
编写于
5月 13, 2020
作者:
Y
Yang Zhang
提交者:
GitHub
5月 13, 2020
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差异文件
Refine `squared_l2_distance_grad` error message (#24418)
test=develop
上级
24cf3932
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1
隐藏空白更改
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并排
Showing
1 changed file
with
15 addition
and
4 deletion
+15
-4
paddle/fluid/operators/squared_l2_distance_op.h
paddle/fluid/operators/squared_l2_distance_op.h
+15
-4
未找到文件。
paddle/fluid/operators/squared_l2_distance_op.h
浏览文件 @
9c3739b0
...
@@ -77,8 +77,16 @@ class SquaredL2DistanceGradKernel : public framework::OpKernel<T> {
...
@@ -77,8 +77,16 @@ class SquaredL2DistanceGradKernel : public framework::OpKernel<T> {
auto
*
x_g
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
x_g
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
y_g
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
*
y_g
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
PADDLE_ENFORCE_NOT_NULL
(
x_g
);
PADDLE_ENFORCE_NOT_NULL
(
PADDLE_ENFORCE_NOT_NULL
(
y_g
);
x_g
,
platform
::
errors
::
NotFound
(
"variable(%s) cannot be found "
"in scope for operator 'squared_l2_distance_grad'."
,
framework
::
GradVarName
(
"X"
)));
PADDLE_ENFORCE_NOT_NULL
(
y_g
,
platform
::
errors
::
NotFound
(
"variable(%s) cannot be found "
"in scope for operator 'squared_l2_distance_grad'."
,
framework
::
GradVarName
(
"Y"
)));
auto
sub_result
=
EigenMatrix
<
T
>::
From
(
*
in0
);
auto
sub_result
=
EigenMatrix
<
T
>::
From
(
*
in0
);
auto
out_grad
=
EigenMatrix
<
T
>::
From
(
*
in1
);
auto
out_grad
=
EigenMatrix
<
T
>::
From
(
*
in1
);
...
@@ -106,8 +114,11 @@ class SquaredL2DistanceGradKernel : public framework::OpKernel<T> {
...
@@ -106,8 +114,11 @@ class SquaredL2DistanceGradKernel : public framework::OpKernel<T> {
y_g
->
mutable_data
<
T
>
(
context
.
GetPlace
());
y_g
->
mutable_data
<
T
>
(
context
.
GetPlace
());
PADDLE_ENFORCE_GE
(
sub_result
.
dimensions
()[
0
],
y_dims
[
0
],
PADDLE_ENFORCE_GE
(
sub_result
.
dimensions
()[
0
],
y_dims
[
0
],
"First dimension of gradient must be greater or "
platform
::
errors
::
InvalidArgument
(
"equal than first dimension of target."
);
"First dimension of gradient must be greater or "
"equal than first dimension of target. But received "
"gradient dimension = %d and target dimension is %d."
,
sub_result
.
dimensions
()[
0
],
y_dims
[
0
]));
if
(
sub_result
.
dimensions
()[
0
]
==
y_dims
[
0
])
{
if
(
sub_result
.
dimensions
()[
0
]
==
y_dims
[
0
])
{
auto
y_grad
=
auto
y_grad
=
...
...
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