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
5f99ae90
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
5f99ae90
编写于
11月 13, 2017
作者:
P
peterzhang2029
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
refine notation in bilinear_tensor_product_op.h
上级
5cf82041
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
11 addition
and
11 deletion
+11
-11
paddle/operators/bilinear_tensor_product_op.h
paddle/operators/bilinear_tensor_product_op.h
+11
-11
未找到文件。
paddle/operators/bilinear_tensor_product_op.h
浏览文件 @
5f99ae90
...
@@ -27,10 +27,6 @@ template <typename T, int MajorType = Eigen::RowMajor,
...
@@ -27,10 +27,6 @@ template <typename T, int MajorType = Eigen::RowMajor,
typename
IndexType
=
Eigen
::
DenseIndex
>
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenMatrix
=
framework
::
EigenMatrix
<
T
,
MajorType
,
IndexType
>
;
using
EigenMatrix
=
framework
::
EigenMatrix
<
T
,
MajorType
,
IndexType
>
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenVector
=
framework
::
EigenVector
<
T
,
MajorType
,
IndexType
>
;
template
<
typename
Place
,
typename
T
>
template
<
typename
Place
,
typename
T
>
class
BilinearTensorProductKernel
:
public
framework
::
OpKernel
<
T
>
{
class
BilinearTensorProductKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
public:
...
@@ -49,7 +45,9 @@ class BilinearTensorProductKernel : public framework::OpKernel<T> {
...
@@ -49,7 +45,9 @@ class BilinearTensorProductKernel : public framework::OpKernel<T> {
auto
weight_dims
=
weight
->
dims
();
auto
weight_dims
=
weight
->
dims
();
auto
place
=
ctx
.
GetEigenDevice
<
Place
>
();
auto
place
=
ctx
.
GetEigenDevice
<
Place
>
();
// Create the intermediate variables.
// Create the intermediate variable to caculate the result of
// Input(X) multiplied by Input(Weight_i), the formula is:
// left_mul = X Weight_i.
Tensor
left_mul
;
Tensor
left_mul
;
left_mul
.
mutable_data
<
T
>
(
framework
::
make_ddim
({
batch_size
,
weight_dims
[
2
]}),
left_mul
.
mutable_data
<
T
>
(
framework
::
make_ddim
({
batch_size
,
weight_dims
[
2
]}),
ctx
.
GetPlace
());
ctx
.
GetPlace
());
...
@@ -95,11 +93,13 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
...
@@ -95,11 +93,13 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
auto
d_out_mat
=
EigenMatrix
<
T
>::
From
(
*
d_out
);
auto
d_out_mat
=
EigenMatrix
<
T
>::
From
(
*
d_out
);
auto
place
=
ctx
.
GetEigenDevice
<
Place
>
();
auto
place
=
ctx
.
GetEigenDevice
<
Place
>
();
// Create the intermediate variable
s for gradient
.
// Create the intermediate variable
to caculate the Output(Y@Grad)
.
Tensor
x_scale
;
Tensor
x_scale
;
x_scale
.
mutable_data
<
T
>
(
framework
::
make_ddim
({
batch_size
,
weight_dims
[
1
]}),
x_scale
.
mutable_data
<
T
>
(
framework
::
make_ddim
({
batch_size
,
weight_dims
[
1
]}),
ctx
.
GetPlace
());
ctx
.
GetPlace
());
auto
x_scale_mat
=
EigenMatrix
<
T
>::
From
(
x_scale
);
auto
x_scale_mat
=
EigenMatrix
<
T
>::
From
(
x_scale
);
// Create the intermediate variable to caculate the Output(X@Grad).
Tensor
y_scale
;
Tensor
y_scale
;
y_scale
.
mutable_data
<
T
>
(
framework
::
make_ddim
({
batch_size
,
weight_dims
[
2
]}),
y_scale
.
mutable_data
<
T
>
(
framework
::
make_ddim
({
batch_size
,
weight_dims
[
2
]}),
ctx
.
GetPlace
());
ctx
.
GetPlace
());
...
@@ -107,19 +107,19 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
...
@@ -107,19 +107,19 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
math
::
SetConstant
<
Place
,
T
>
set_zero
;
math
::
SetConstant
<
Place
,
T
>
set_zero
;
// Set
X@Grad be zero at first
.
// Set
Output(X@Grad) be zero
.
if
(
d_x
)
{
if
(
d_x
)
{
d_x
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
d_x
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
set_zero
(
ctx
.
device_context
(),
d_x
,
static_cast
<
T
>
(
0
));
set_zero
(
ctx
.
device_context
(),
d_x
,
static_cast
<
T
>
(
0
));
}
}
// Set
Y@Grad be zero at first
.
// Set
Output(Y@Grad) be zero
.
if
(
d_y
)
{
if
(
d_y
)
{
d_y
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
d_y
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
set_zero
(
ctx
.
device_context
(),
d_y
,
static_cast
<
T
>
(
0
));
set_zero
(
ctx
.
device_context
(),
d_y
,
static_cast
<
T
>
(
0
));
}
}
// Caculate the
X@Grad and Y@Grad
.
// Caculate the
Output(X@Grad) and Output(Y@Grad)
.
if
(
d_x
||
d_y
)
{
if
(
d_x
||
d_y
)
{
Eigen
::
DSizes
<
int
,
2
>
bcast_for_x
(
1
,
weight_dims
[
2
]);
Eigen
::
DSizes
<
int
,
2
>
bcast_for_x
(
1
,
weight_dims
[
2
]);
Eigen
::
DSizes
<
int
,
2
>
bcast_for_y
(
1
,
weight_dims
[
1
]);
Eigen
::
DSizes
<
int
,
2
>
bcast_for_y
(
1
,
weight_dims
[
1
]);
...
@@ -150,7 +150,7 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
...
@@ -150,7 +150,7 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
}
}
}
}
// Caculate the gradient of
Weight
.
// Caculate the gradient of
Input(Weight)
.
if
(
d_weight
)
{
if
(
d_weight
)
{
d_weight
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
d_weight
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
Eigen
::
DSizes
<
int
,
2
>
bcast_for_weight
(
1
,
weight_dims
[
1
]);
Eigen
::
DSizes
<
int
,
2
>
bcast_for_weight
(
1
,
weight_dims
[
1
]);
...
@@ -169,7 +169,7 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
...
@@ -169,7 +169,7 @@ class BilinearTensorProductGradKernel : public framework::OpKernel<T> {
}
}
}
}
// Caculate the gradient of
Bias
.
// Caculate the gradient of
Input(Bias)
.
if
(
d_bias
)
{
if
(
d_bias
)
{
d_bias
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
d_bias
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
d_bias_mat
=
EigenMatrix
<
T
>::
From
(
*
d_bias
);
auto
d_bias_mat
=
EigenMatrix
<
T
>::
From
(
*
d_bias
);
...
...
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