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06ddaa73
编写于
4月 13, 2018
作者:
Y
Yu Yang
提交者:
GitHub
4月 13, 2018
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差异文件
Merge pull request #9840 from reyoung/feature/polish_reshape_op
Polish reshape op
上级
6f0df4fd
daa50117
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
4 addition
and
2 deletion
+4
-2
paddle/fluid/operators/reshape_op.h
paddle/fluid/operators/reshape_op.h
+4
-2
未找到文件。
paddle/fluid/operators/reshape_op.h
浏览文件 @
06ddaa73
...
@@ -60,7 +60,7 @@ class ReshapeOp : public framework::OperatorWithKernel {
...
@@ -60,7 +60,7 @@ class ReshapeOp : public framework::OperatorWithKernel {
static
framework
::
DDim
ValidateShape
(
const
std
::
vector
<
int
>
shape
,
static
framework
::
DDim
ValidateShape
(
const
std
::
vector
<
int
>
shape
,
const
framework
::
DDim
&
in_dims
)
{
const
framework
::
DDim
&
in_dims
)
{
const
int64_t
in_size
=
framework
::
product
(
in_dims
);
const
int64_t
in_size
=
framework
::
product
(
in_dims
);
// only one dimension canbe set to -1, whose size will be automatically
// only one dimension can
be set to -1, whose size will be automatically
// infered.
// infered.
const
int64_t
unk_dim_val
=
-
1
;
const
int64_t
unk_dim_val
=
-
1
;
const
int64_t
copy_dim_val
=
0
;
const
int64_t
copy_dim_val
=
0
;
...
@@ -119,13 +119,15 @@ class ReshapeKernel : public framework::OpKernel<T> {
...
@@ -119,13 +119,15 @@ class ReshapeKernel : public framework::OpKernel<T> {
auto
*
shape_tensor
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"Shape"
);
auto
*
shape_tensor
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"Shape"
);
framework
::
DDim
out_dims
=
out
->
dims
();
framework
::
DDim
out_dims
=
out
->
dims
();
if
(
shape_tensor
)
{
if
(
shape_tensor
)
{
auto
*
shape_data
=
shape_tensor
->
data
<
int
>
();
auto
*
shape_data
=
shape_tensor
->
data
<
int
>
();
framework
::
Tensor
cpu_shape_tensor
;
if
(
platform
::
is_gpu_place
(
ctx
.
GetPlace
()))
{
if
(
platform
::
is_gpu_place
(
ctx
.
GetPlace
()))
{
framework
::
Tensor
cpu_shape_tensor
;
TensorCopy
(
*
shape_tensor
,
platform
::
CPUPlace
(),
ctx
.
device_context
(),
TensorCopy
(
*
shape_tensor
,
platform
::
CPUPlace
(),
ctx
.
device_context
(),
&
cpu_shape_tensor
);
&
cpu_shape_tensor
);
shape_data
=
cpu_shape_tensor
.
data
<
int
>
();
shape_data
=
cpu_shape_tensor
.
data
<
int
>
();
ctx
.
device_context
().
Wait
();
}
}
auto
shape
=
auto
shape
=
std
::
vector
<
int
>
(
shape_data
,
shape_data
+
shape_tensor
->
numel
());
std
::
vector
<
int
>
(
shape_data
,
shape_data
+
shape_tensor
->
numel
());
...
...
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