Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
wzpei9
Paddle
提交
d6a0280e
P
Paddle
项目概览
wzpei9
/
Paddle
与 Fork 源项目一致
Fork自
PaddlePaddle / Paddle
通知
1
Star
1
Fork
0
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
1
列表
看板
标记
里程碑
合并请求
0
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
1
Issue
1
列表
看板
标记
里程碑
合并请求
0
合并请求
0
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
提交
d6a0280e
编写于
9月 15, 2017
作者:
D
dangqingqing
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Enhance unit testing framework for operator with LoDTensor.
上级
40fba4aa
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
22 addition
and
10 deletion
+22
-10
paddle/operators/sequence_avg_pool_op.cc
paddle/operators/sequence_avg_pool_op.cc
+3
-1
paddle/operators/sequence_avg_pool_op.h
paddle/operators/sequence_avg_pool_op.h
+8
-5
python/paddle/v2/framework/tests/op_test.py
python/paddle/v2/framework/tests/op_test.py
+11
-4
未找到文件。
paddle/operators/sequence_avg_pool_op.cc
浏览文件 @
d6a0280e
...
...
@@ -60,7 +60,9 @@ class SequenceAvgPoolGradOp : public framework::OperatorWithKernel {
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
framework
::
GradVarName
(
"Out"
)),
"Gradient of Out should not be null"
);
"Gradient of Out should not be null."
);
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"X"
),
"The input X should not be null."
);
auto
og_dims
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
();
auto
x_dims
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
)
->
dims
();
...
...
paddle/operators/sequence_avg_pool_op.h
浏览文件 @
d6a0280e
...
...
@@ -21,6 +21,9 @@ namespace operators {
using
Tensor
=
framework
::
Tensor
;
using
LoDTensor
=
framework
::
LoDTensor
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenVector
=
framework
::
EigenVector
<
T
,
MajorType
,
IndexType
>
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenMatrix
=
framework
::
EigenMatrix
<
T
,
MajorType
,
IndexType
>
;
...
...
@@ -43,8 +46,8 @@ class SequenceAvgPoolKernel : public framework::OpKernel {
static_cast
<
int
>
(
lod
[
0
][
i
+
1
]));
Tensor
out_t
=
out
->
Slice
<
T
>
(
i
,
i
+
1
);
int64_t
h
=
static_cast
<
int64_t
>
(
lod
[
0
][
i
+
1
]
-
lod
[
0
][
i
]);
auto
in_e
=
EigenMatrix
<
T
>::
From
(
in_t
,
{
h
,
w
}
);
auto
out_e
=
Eigen
Matrix
<
T
>::
From
(
out_t
,
{
h
,
w
}
);
auto
in_e
=
EigenMatrix
<
T
>::
From
(
in_t
,
framework
::
make_ddim
({
h
,
w
})
);
auto
out_e
=
Eigen
Vector
<
T
>::
Flatten
(
out_t
);
out_e
.
device
(
place
)
=
in_e
.
mean
(
Eigen
::
array
<
int
,
1
>
({{
0
}}));
}
}
...
...
@@ -54,9 +57,9 @@ template <typename Place, typename T>
class
SequenceAvgPoolGradKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
*
in
=
context
.
Output
<
LoDTensor
>
(
"X"
);
auto
*
in_g
=
context
.
Output
<
LoDTensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
in
=
context
.
Input
<
LoDTensor
>
(
"X"
);
auto
*
out_g
=
context
.
Input
<
LoDTensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
in_g
=
context
.
Output
<
LoDTensor
>
(
framework
::
GradVarName
(
"X"
));
auto
dims
=
in
->
dims
();
auto
lod
=
in
->
lod
();
...
...
@@ -71,7 +74,7 @@ class SequenceAvgPoolGradKernel : public framework::OpKernel {
int64_t
h
=
static_cast
<
int64_t
>
(
lod
[
0
][
i
+
1
]
-
lod
[
0
][
i
]);
auto
in_g_e
=
EigenMatrix
<
T
>::
From
(
in_g_t
,
{
h
,
w
});
auto
out_g_e
=
EigenMatrix
<
T
>::
From
(
out_g_t
,
{
1
,
w
});
Eigen
::
DSizes
<
int
,
2
>
bcast
(
h
,
w
);
Eigen
::
DSizes
<
int
,
2
>
bcast
(
h
,
1
);
in_g_e
.
device
(
place
)
=
(
out_g_e
/
static_cast
<
T
>
(
h
)).
broadcast
(
bcast
);
}
}
...
...
python/paddle/v2/framework/tests/op_test.py
浏览文件 @
d6a0280e
...
...
@@ -47,17 +47,24 @@ def set_input(scope, op, inputs, place):
if
in_name
in
inputs
:
if
in_dup
:
sub_in
=
inputs
[
in_name
]
for
sub_in_name
,
sub_in_
array
in
sub_in
:
for
sub_in_name
,
sub_in_
val
in
sub_in
:
var
=
scope
.
find_var
(
sub_in_name
)
tensor
=
var
.
get_tensor
()
sub_in_array
=
sub_in_val
[
0
]
\
if
isinstance
(
sub_in_val
,
tuple
)
else
sub_in_val
tensor
.
set_dims
(
sub_in_array
.
shape
)
tensor
.
set
(
sub_in_array
,
place
)
if
isinstance
(
sub_in_val
,
tuple
):
tensor
.
set_lod
(
sub_in_val
[
1
])
else
:
var
=
scope
.
find_var
(
in_name
)
tensor
=
var
.
get_tensor
()
arr
=
inputs
[
in_name
]
tensor
.
set_dims
(
arr
.
shape
)
tensor
.
set
(
arr
,
place
)
in_val
=
inputs
[
in_name
]
in_array
=
in_val
[
0
]
if
isinstance
(
in_val
,
tuple
)
else
in_val
tensor
.
set_dims
(
in_array
.
shape
)
tensor
.
set
(
in_array
,
place
)
if
isinstance
(
in_val
,
tuple
):
tensor
.
set_lod
(
in_val
[
1
])
def
set_output_grad
(
scope
,
op
,
outputs
,
place
):
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录