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
夏有凉风,冬有雪
Paddle
提交
458a2da3
P
Paddle
项目概览
夏有凉风,冬有雪
/
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
458a2da3
编写于
10月 11, 2017
作者:
F
fengjiayi
浏览文件
操作
浏览文件
下载
差异文件
Merge branch 'fix_bugs' into dev_opdesc_in_python
上级
752bab27
2434e486
变更
19
隐藏空白更改
内联
并排
Showing
19 changed file
with
220 addition
and
88 deletion
+220
-88
paddle/framework/tensor.h
paddle/framework/tensor.h
+11
-6
paddle/framework/tensor_array.cc
paddle/framework/tensor_array.cc
+10
-5
paddle/framework/tensor_impl.h
paddle/framework/tensor_impl.h
+35
-16
paddle/framework/tensor_test.cc
paddle/framework/tensor_test.cc
+27
-17
paddle/framework/var_desc.h
paddle/framework/var_desc.h
+2
-0
paddle/operators/activation_op.cc
paddle/operators/activation_op.cc
+21
-0
paddle/operators/activation_op.h
paddle/operators/activation_op.h
+28
-1
paddle/operators/feed_op.h
paddle/operators/feed_op.h
+1
-1
paddle/operators/fetch_op.h
paddle/operators/fetch_op.h
+2
-1
paddle/operators/math/im2col_test.cc
paddle/operators/math/im2col_test.cc
+17
-15
paddle/operators/math/math_function_test.cc
paddle/operators/math/math_function_test.cc
+18
-14
paddle/operators/multiplex_op.cu
paddle/operators/multiplex_op.cu
+4
-2
paddle/operators/recurrent_op.cc
paddle/operators/recurrent_op.cc
+3
-3
paddle/operators/reshape_op.h
paddle/operators/reshape_op.h
+2
-2
paddle/operators/rnn/recurrent_op_utils.cc
paddle/operators/rnn/recurrent_op_utils.cc
+2
-2
paddle/operators/rnn/recurrent_op_utils.h
paddle/operators/rnn/recurrent_op_utils.h
+1
-1
paddle/operators/uniform_random_op.cc
paddle/operators/uniform_random_op.cc
+1
-1
paddle/pybind/tensor_py.h
paddle/pybind/tensor_py.h
+14
-1
python/paddle/v2/framework/tests/test_activation_op.py
python/paddle/v2/framework/tests/test_activation_op.py
+21
-0
未找到文件。
paddle/framework/tensor.h
浏览文件 @
458a2da3
...
...
@@ -87,26 +87,31 @@ class Tensor {
/**
* @brief Copy the content of external tensor to a new place.
*
* @param[in] src The external tensor.
* @param[in] ctx The device context contains place where to store.
* @param[in] src The external tensor.
* @param[in] dst_place The dst place.
* @param[in] ctx The device context contains device resources.
*
* @note CopyFrom supports CPU <-> GPU, GPU <-> GPU.
*/
// TODO(qijun): https://github.com/PaddlePaddle/Paddle/issues/4647
// Remove `CopyFrom` and `CopyFromVector` from Tensor interface
// and make them global functions
template
<
typename
T
>
inline
void
CopyFrom
(
const
Tensor
&
src
,
const
platform
::
Place
&
dst_place
);
inline
void
CopyFrom
(
const
Tensor
&
src
,
const
platform
::
Place
&
dst_place
,
const
platform
::
DeviceContext
&
ctx
);
/**
* @brief Copy the content of an external vector to a tensor.
*
* @param[in] src
The external vect
or.
* @param[in] ctx
The device context contains place where to store
.
* @param[in] src
The external tens
or.
* @param[in] ctx
The device context contains device resources
.
*
* * @note CopyFromVector assumes that the tensor has been resized
* before invoking.
*/
template
<
typename
T
>
inline
void
CopyFromVector
(
const
std
::
vector
<
T
>&
src
,
const
platform
::
Place
&
dst_place
);
const
platform
::
DeviceContext
&
ctx
);
/**
* @brief Return the slice of the tensor.
...
...
paddle/framework/tensor_array.cc
浏览文件 @
458a2da3
...
...
@@ -95,7 +95,8 @@ void TensorArray::Write(size_t index, const LoDTensor& value) {
values_
[
index
].
Resize
(
value
.
dims
());
values_
[
index
].
mutable_data
<
value_type
>
(
platform
::
CPUPlace
());
values_
[
index
].
CopyFrom
<
value_type
>
(
value
,
platform
::
CPUPlace
());
values_
[
index
].
CopyFrom
<
value_type
>
(
value
,
platform
::
CPUPlace
(),
platform
::
CPUDeviceContext
());
}
void
TensorArray
::
WriteShared
(
size_t
index
,
const
LoDTensor
&
value
)
{
...
...
@@ -151,7 +152,8 @@ LoDTensor TensorArray::Stack() const {
for
(
size_t
idx
=
0
;
idx
<
size
();
idx
++
)
{
result
.
Slice
<
value_type
>
(
idx
,
idx
+
1
)
.
CopyFrom
<
value_type
>
(
Read
(
idx
),
platform
::
CPUPlace
());
.
CopyFrom
<
value_type
>
(
Read
(
idx
),
platform
::
CPUPlace
(),
platform
::
CPUDeviceContext
());
}
return
result
;
}
...
...
@@ -182,7 +184,8 @@ void TensorArray::Unstack(const LoDTensor& source, bool data_shared) const {
// copy
value
.
Resize
(
value_dims
);
value
.
CopyFrom
<
value_type
>
(
source
.
Slice
<
value_type
>
(
elem
,
elem
+
1
),
platform
::
CPUPlace
());
platform
::
CPUPlace
(),
platform
::
CPUDeviceContext
());
}
}
}
...
...
@@ -236,7 +239,8 @@ LoDTensor DynamicBatchUnpacker::GetBatch(size_t index) {
auto
target
=
result
.
Slice
<
value_type
>
(
i
,
i
+
1
);
auto
source_
=
source
->
Slice
<
value_type
>
(
index
,
index
+
1
);
target
.
CopyFrom
<
value_type
>
(
source_
,
platform
::
CPUPlace
());
target
.
CopyFrom
<
value_type
>
(
source_
,
platform
::
CPUPlace
(),
platform
::
CPUDeviceContext
());
}
return
result
;
...
...
@@ -269,7 +273,8 @@ LoDTensor PackDynamicBatch(const std::vector<LoDTensor>& source,
if
(
index
>=
seq_meta
.
end
)
break
;
auto
source_
=
source
[
batch_id
].
Slice
<
float
>
(
seq_id
,
seq_id
+
1
);
auto
target
=
result
.
Slice
<
float
>
(
index
,
index
+
1
);
target
.
CopyFrom
<
float
>
(
source_
,
platform
::
CPUPlace
());
target
.
CopyFrom
<
float
>
(
source_
,
platform
::
CPUPlace
(),
platform
::
CPUDeviceContext
());
}
}
...
...
paddle/framework/tensor_impl.h
浏览文件 @
458a2da3
...
...
@@ -88,7 +88,8 @@ inline Tensor& Tensor::ShareDataWith(const Tensor& src) {
template
<
typename
T
>
inline
void
Tensor
::
CopyFrom
(
const
Tensor
&
src
,
const
platform
::
Place
&
dst_place
)
{
const
platform
::
Place
&
dst_place
,
const
platform
::
DeviceContext
&
ctx
)
{
src
.
check_memory_size
<
T
>
();
Resize
(
src
.
dims
());
...
...
@@ -106,26 +107,45 @@ inline void Tensor::CopyFrom(const Tensor& src,
#ifdef PADDLE_WITH_CUDA
else
if
(
platform
::
is_gpu_place
(
src_place
)
&&
platform
::
is_cpu_place
(
dst_place
))
{
memory
::
Copy
(
boost
::
get
<
platform
::
CPUPlace
>
(
dst_place
),
dst_ptr
,
boost
::
get
<
platform
::
GPUPlace
>
(
src_place
),
src_ptr
,
size
,
0
);
auto
src_gpu_place
=
boost
::
get
<
platform
::
GPUPlace
>
(
src_place
);
auto
dst_cpu_place
=
boost
::
get
<
platform
::
CPUPlace
>
(
dst_place
);
auto
ctx_place
=
ctx
.
GetPlace
();
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
ctx_place
));
auto
ctx_gpu_place
=
boost
::
get
<
platform
::
GPUPlace
>
(
ctx_place
);
PADDLE_ENFORCE_EQ
(
src_gpu_place
,
ctx_gpu_place
);
memory
::
Copy
(
dst_cpu_place
,
dst_ptr
,
src_gpu_place
,
src_ptr
,
size
,
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
ctx
).
stream
());
}
else
if
(
platform
::
is_cpu_place
(
src_place
)
&&
platform
::
is_gpu_place
(
dst_place
))
{
memory
::
Copy
(
boost
::
get
<
platform
::
GPUPlace
>
(
dst_place
),
dst_ptr
,
boost
::
get
<
platform
::
CPUPlace
>
(
src_place
),
src_ptr
,
size
,
0
);
auto
src_cpu_place
=
boost
::
get
<
platform
::
CPUPlace
>
(
src_place
);
auto
dst_gpu_place
=
boost
::
get
<
platform
::
GPUPlace
>
(
dst_place
);
auto
ctx_place
=
ctx
.
GetPlace
();
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
ctx_place
));
auto
ctx_gpu_place
=
boost
::
get
<
platform
::
GPUPlace
>
(
ctx_place
);
PADDLE_ENFORCE_EQ
(
dst_gpu_place
,
ctx_gpu_place
);
memory
::
Copy
(
dst_gpu_place
,
dst_ptr
,
src_cpu_place
,
src_ptr
,
size
,
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
ctx
).
stream
());
}
else
if
(
platform
::
is_gpu_place
(
src_place
)
&&
platform
::
is_gpu_place
(
dst_place
))
{
memory
::
Copy
(
boost
::
get
<
platform
::
GPUPlace
>
(
dst_place
),
dst_ptr
,
boost
::
get
<
platform
::
GPUPlace
>
(
src_place
),
src_ptr
,
size
,
0
);
auto
src_gpu_place
=
boost
::
get
<
platform
::
GPUPlace
>
(
src_place
);
auto
dst_gpu_place
=
boost
::
get
<
platform
::
GPUPlace
>
(
dst_place
);
auto
ctx_place
=
ctx
.
GetPlace
();
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
ctx_place
));
auto
ctx_gpu_place
=
boost
::
get
<
platform
::
GPUPlace
>
(
ctx_place
);
PADDLE_ENFORCE_EQ
(
src_gpu_place
,
ctx_gpu_place
);
memory
::
Copy
(
dst_gpu_place
,
dst_ptr
,
src_gpu_place
,
src_ptr
,
size
,
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
ctx
).
stream
());
}
PADDLE_ENFORCE
(
cudaStreamSynchronize
(
0
),
"cudaStreamSynchronize failed in Tensor CopyFrom"
);
#endif
}
template
<
typename
T
>
inline
void
Tensor
::
CopyFromVector
(
const
std
::
vector
<
T
>&
src
,
const
platform
::
Place
&
dst_place
)
{
const
platform
::
DeviceContext
&
ctx
)
{
auto
dst_place
=
ctx
.
GetPlace
();
auto
src_ptr
=
static_cast
<
const
void
*>
(
src
.
data
());
platform
::
CPUPlace
src_place
;
auto
dst_ptr
=
static_cast
<
void
*>
(
mutable_data
<
T
>
(
dst_place
));
...
...
@@ -137,12 +157,11 @@ inline void Tensor::CopyFromVector(const std::vector<T>& src,
}
#ifdef PADDLE_WITH_CUDA
else
if
(
platform
::
is_gpu_place
(
dst_place
))
{
memory
::
Copy
(
boost
::
get
<
platform
::
GPUPlace
>
(
dst_place
),
dst_ptr
,
src_place
,
src_ptr
,
size
,
0
);
memory
::
Copy
(
boost
::
get
<
platform
::
GPUPlace
>
(
dst_place
),
dst_ptr
,
src_place
,
src_ptr
,
size
,
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
ctx
).
stream
());
}
PADDLE_ENFORCE
(
cudaStreamSynchronize
(
0
),
"cudaStreamSynchronize failed in Tensor CopyFromVector"
);
#endif
}
...
...
paddle/framework/tensor_test.cc
浏览文件 @
458a2da3
...
...
@@ -194,6 +194,7 @@ TEST(Tensor, CopyFrom) {
{
Tensor
src_tensor
;
Tensor
dst_tensor
;
CPUDeviceContext
cpu_ctx
((
CPUPlace
()));
int
*
src_ptr
=
src_tensor
.
mutable_data
<
int
>
(
make_ddim
({
3
,
3
}),
CPUPlace
());
...
...
@@ -201,7 +202,7 @@ TEST(Tensor, CopyFrom) {
memcpy
(
src_ptr
,
arr
,
9
*
sizeof
(
int
));
auto
cpu_place
=
new
paddle
::
platform
::
CPUPlace
();
dst_tensor
.
CopyFrom
<
int
>
(
src_tensor
,
*
cpu_place
);
dst_tensor
.
CopyFrom
<
int
>
(
src_tensor
,
*
cpu_place
,
cpu_ctx
);
const
int
*
dst_ptr
=
dst_tensor
.
data
<
int
>
();
ASSERT_NE
(
src_ptr
,
dst_ptr
);
...
...
@@ -210,7 +211,7 @@ TEST(Tensor, CopyFrom) {
}
Tensor
slice_tensor
=
src_tensor
.
Slice
<
int
>
(
1
,
2
);
dst_tensor
.
CopyFrom
<
int
>
(
slice_tensor
,
*
cpu_place
);
dst_tensor
.
CopyFrom
<
int
>
(
slice_tensor
,
*
cpu_place
,
cpu_ctx
);
const
int
*
slice_ptr
=
slice_tensor
.
data
<
int
>
();
dst_ptr
=
dst_tensor
.
data
<
int
>
();
ASSERT_NE
(
dst_ptr
,
slice_ptr
);
...
...
@@ -231,13 +232,15 @@ TEST(Tensor, CopyFrom) {
// CPU Tensor to GPU Tensor
auto
gpu_place
=
new
paddle
::
platform
::
GPUPlace
(
0
);
gpu_tensor
.
CopyFrom
<
int
>
(
src_tensor
,
*
gpu_place
);
CUDADeviceContext
gpu_ctx
(
*
gpu_place
);
gpu_tensor
.
CopyFrom
<
int
>
(
src_tensor
,
*
gpu_place
,
gpu_ctx
);
// GPU Tensor to CPU Tensor
auto
cpu_place
=
new
paddle
::
platform
::
CPUPlace
();
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
);
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
,
gpu_ctx
);
// Compare Tensors
// Sync before Compare Tensors
gpu_ctx
.
Wait
();
const
int
*
dst_ptr
=
dst_tensor
.
data
<
int
>
();
ASSERT_NE
(
src_ptr
,
dst_ptr
);
for
(
size_t
i
=
0
;
i
<
9
;
++
i
)
{
...
...
@@ -247,12 +250,13 @@ TEST(Tensor, CopyFrom) {
Tensor
slice_tensor
=
src_tensor
.
Slice
<
int
>
(
1
,
2
);
// CPU Slice Tensor to GPU Tensor
gpu_tensor
.
CopyFrom
<
int
>
(
slice_tensor
,
*
gpu_place
);
gpu_tensor
.
CopyFrom
<
int
>
(
slice_tensor
,
*
gpu_place
,
gpu_ctx
);
// GPU Tensor to CPU Tensor
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
);
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
,
gpu_ctx
);
// Compare Slice Tensors
// Sync before Compare Slice Tensors
gpu_ctx
.
Wait
();
const
int
*
slice_ptr
=
slice_tensor
.
data
<
int
>
();
dst_ptr
=
dst_tensor
.
data
<
int
>
();
ASSERT_NE
(
dst_ptr
,
slice_ptr
);
...
...
@@ -273,7 +277,8 @@ TEST(Tensor, CopyFromVector) {
// Copy to CPU Tensor
cpu_tensor
.
Resize
(
make_ddim
({
3
,
3
}));
auto
cpu_place
=
new
paddle
::
platform
::
CPUPlace
();
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
*
cpu_place
);
CPUDeviceContext
cpu_ctx
(
*
cpu_place
);
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
cpu_ctx
);
// Compare Tensors
const
int
*
cpu_ptr
=
cpu_tensor
.
data
<
int
>
();
...
...
@@ -285,7 +290,7 @@ TEST(Tensor, CopyFromVector) {
src_vec
.
erase
(
src_vec
.
begin
(),
src_vec
.
begin
()
+
5
);
cpu_tensor
.
Resize
(
make_ddim
({
2
,
2
}));
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
*
cpu_place
);
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
cpu_ctx
);
cpu_ptr
=
cpu_tensor
.
data
<
int
>
();
src_ptr
=
src_vec
.
data
();
ASSERT_NE
(
src_ptr
,
cpu_ptr
);
...
...
@@ -306,16 +311,19 @@ TEST(Tensor, CopyFromVector) {
// Copy to CPU Tensor
cpu_tensor
.
Resize
(
make_ddim
({
3
,
3
}));
auto
cpu_place
=
new
paddle
::
platform
::
CPUPlace
();
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
*
cpu_place
);
CPUDeviceContext
cpu_ctx
(
*
cpu_place
);
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
cpu_ctx
);
// Copy to GPUTensor
gpu_tensor
.
Resize
(
make_ddim
({
3
,
3
}));
auto
gpu_place
=
new
paddle
::
platform
::
GPUPlace
();
gpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
*
gpu_place
);
CUDADeviceContext
gpu_ctx
(
*
gpu_place
);
gpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
gpu_ctx
);
// Copy from GPU to CPU tensor for comparison
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
);
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
,
gpu_ctx
);
// Compare Tensors
// Sync before Compare Tensors
gpu_ctx
.
Wait
();
const
int
*
src_ptr
=
src_vec
.
data
();
const
int
*
cpu_ptr
=
cpu_tensor
.
data
<
int
>
();
const
int
*
dst_ptr
=
dst_tensor
.
data
<
int
>
();
...
...
@@ -329,11 +337,13 @@ TEST(Tensor, CopyFromVector) {
src_vec
.
erase
(
src_vec
.
begin
(),
src_vec
.
begin
()
+
5
);
cpu_tensor
.
Resize
(
make_ddim
({
2
,
2
}));
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
*
cpu_place
);
cpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
cpu_ctx
);
gpu_tensor
.
Resize
(
make_ddim
({
2
,
2
}));
gpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
*
gpu_place
);
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
);
gpu_tensor
.
CopyFromVector
<
int
>
(
src_vec
,
gpu_ctx
);
dst_tensor
.
CopyFrom
<
int
>
(
gpu_tensor
,
*
cpu_place
,
gpu_ctx
);
// Sync before Compare Tensors
gpu_ctx
.
Wait
();
src_ptr
=
src_vec
.
data
();
cpu_ptr
=
cpu_tensor
.
data
<
int
>
();
dst_ptr
=
dst_tensor
.
data
<
int
>
();
...
...
paddle/framework/var_desc.h
浏览文件 @
458a2da3
...
...
@@ -34,6 +34,7 @@ inline std::vector<T> RepeatedToVector(
template
<
typename
T
,
typename
RepeatedField
>
inline
void
VectorToRepeated
(
const
std
::
vector
<
T
>
&
vec
,
RepeatedField
*
repeated_field
)
{
repeated_field
->
Clear
();
repeated_field
->
Reserve
(
vec
.
size
());
for
(
const
auto
&
elem
:
vec
)
{
*
repeated_field
->
Add
()
=
elem
;
...
...
@@ -44,6 +45,7 @@ inline void VectorToRepeated(const std::vector<T> &vec,
template
<
typename
RepeatedField
>
inline
void
VectorToRepeated
(
const
std
::
vector
<
bool
>
&
vec
,
RepeatedField
*
repeated_field
)
{
repeated_field
->
Clear
();
repeated_field
->
Reserve
(
vec
.
size
());
for
(
auto
elem
:
vec
)
{
*
repeated_field
->
Add
()
=
elem
;
...
...
paddle/operators/activation_op.cc
浏览文件 @
458a2da3
...
...
@@ -321,6 +321,23 @@ class STanhOpMaker : public framework::OpProtoAndCheckerMaker {
}
};
template
<
typename
AttrType
>
class
ThresholdedReluOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ThresholdedReluOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of ThresholdedRelu operator"
);
AddOutput
(
"Y"
,
"Output of ThresholdedRelu operator"
);
AddComment
(
"ThresholdedRelu activation operator, "
"thresholded_relu = x for x > threshold, "
"thresholded_relu = 0 otherwise."
);
AddAttr
<
AttrType
>
(
"threshold"
,
"The threshold location of activation"
)
.
SetDefault
(
static_cast
<
AttrType
>
(
1.0
));
}
};
}
// namespace operators
}
// namespace paddle
...
...
@@ -392,6 +409,10 @@ REGISTER_OP(stanh, ops::ActivationOp, ops::STanhOpMaker<float>, stanh_grad,
REGISTER_OP
(
hard_shrink
,
ops
::
ActivationOp
,
ops
::
HardShrinkOpMaker
<
float
>
,
hard_shrink_grad
,
ops
::
ActivationOpGrad
);
REGISTER_OP
(
thresholded_relu
,
ops
::
ActivationOp
,
ops
::
ThresholdedReluOpMaker
<
float
>
,
thresholded_relu_grad
,
ops
::
ActivationOpGrad
);
#define REGISTER_ACTIVATION_CPU_KERNEL(act_type, functor, grad_functor) \
REGISTER_OP_CPU_KERNEL( \
act_type, \
...
...
paddle/operators/activation_op.h
浏览文件 @
458a2da3
...
...
@@ -590,6 +590,32 @@ struct STanhGradFunctor : public BaseActivationFunctor<T> {
}
};
template
<
typename
T
>
struct
ThresholdedReluFunctor
:
public
BaseActivationFunctor
<
T
>
{
float
threshold
;
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"threshold"
,
&
threshold
}};
}
template
<
typename
Device
,
typename
X
,
typename
Y
>
void
operator
()(
Device
d
,
X
x
,
Y
y
)
const
{
y
.
device
(
d
)
=
(
x
>
static_cast
<
T
>
(
threshold
)).
template
cast
<
T
>()
*
x
;
}
};
template
<
typename
T
>
struct
ThresholdedReluGradFunctor
:
public
BaseActivationFunctor
<
T
>
{
float
threshold
;
typename
BaseActivationFunctor
<
T
>::
AttrPair
GetAttrs
()
{
return
{{
"threshold"
,
&
threshold
}};
}
template
<
typename
Device
,
typename
X
,
typename
Y
,
typename
dY
,
typename
dX
>
void
operator
()(
Device
d
,
X
x
,
Y
y
,
dY
dy
,
dX
dx
)
const
{
dx
.
device
(
d
)
=
dy
*
(
x
>
static_cast
<
T
>
(
threshold
)).
template
cast
<
T
>();
}
};
}
// namespace operators
}
// namespace paddle
...
...
@@ -615,4 +641,5 @@ struct STanhGradFunctor : public BaseActivationFunctor<T> {
__macro(leaky_relu, LeakyReluFunctor, LeakyReluGradFunctor); \
__macro(tanh_shrink, TanhShrinkFunctor, TanhShrinkGradFunctor); \
__macro(elu, ELUFunctor, ELUGradFunctor); \
__macro(hard_shrink, HardShrinkFunctor, HardShrinkGradFunctor)
__macro(hard_shrink, HardShrinkFunctor, HardShrinkGradFunctor); \
__macro(thresholded_relu, ThresholdedReluFunctor, ThresholdedReluGradFunctor);
paddle/operators/feed_op.h
浏览文件 @
458a2da3
...
...
@@ -34,7 +34,7 @@ class FeedKernel : public framework::OpKernel<T> {
// TODO(qijun):
// check tensors[col].dims() with attribute,
// except the first dimenson.
out
->
CopyFrom
<
T
>
(
tensors
[
col
],
ctx
.
GetPlace
());
out
->
CopyFrom
<
T
>
(
tensors
[
col
],
ctx
.
GetPlace
()
,
ctx
.
device_context
()
);
}
};
...
...
paddle/operators/fetch_op.h
浏览文件 @
458a2da3
...
...
@@ -35,7 +35,8 @@ class FetchKernel : public framework::OpKernel<T> {
PADDLE_ENFORCE_GT
(
tensors
->
size
(),
static_cast
<
size_t
>
(
col
));
(
*
tensors
)[
col
].
Resize
(
input
->
dims
());
(
*
tensors
)[
col
].
mutable_data
<
T
>
(
platform
::
CPUPlace
());
(
*
tensors
)[
col
].
CopyFrom
<
T
>
(
*
input
,
platform
::
CPUPlace
());
(
*
tensors
)[
col
].
CopyFrom
<
T
>
(
*
input
,
platform
::
CPUPlace
(),
ctx
.
device_context
());
// TODO(qijun): need to handle LodTensor later
}
};
...
...
paddle/operators/math/im2col_test.cc
浏览文件 @
458a2da3
...
...
@@ -49,10 +49,22 @@ void testIm2col() {
memcpy
(
input_ptr
,
arr
,
6
*
sizeof
(
float
));
auto
*
place
=
new
Place
();
paddle
::
platform
::
DeviceContext
*
context
;
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
context
=
new
paddle
::
platform
::
CPUDeviceContext
(
paddle
::
platform
::
CPUPlace
());
}
else
{
#ifdef PADDLE_WITH_CUDA
context
=
new
paddle
::
platform
::
CUDADeviceContext
(
paddle
::
platform
::
GPUPlace
());
#else
PADDLE_THROW
(
"no GPU support"
);
#endif // PADDLE_ONLY_CPU
}
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
input
=
input_tmp
;
}
else
{
input
.
CopyFrom
<
float
>
(
input_tmp
,
*
place
);
input
.
CopyFrom
<
float
>
(
input_tmp
,
*
place
,
*
context
);
}
output_cfo
.
mutable_data
<
float
>
(
{
1
,
filter_size
,
filter_size
,
output_height
,
output_width
},
*
place
);
...
...
@@ -66,18 +78,6 @@ void testIm2col() {
paddle
::
operators
::
math
::
ColFormat
::
kOCF
,
Place
,
float
>
im2col_ocf
;
paddle
::
platform
::
DeviceContext
*
context
;
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
context
=
new
paddle
::
platform
::
CPUDeviceContext
(
paddle
::
platform
::
CPUPlace
());
}
else
{
#ifdef PADDLE_WITH_CUDA
context
=
new
paddle
::
platform
::
CUDADeviceContext
(
paddle
::
platform
::
GPUPlace
());
#else
PADDLE_THROW
(
"no GPU support"
);
#endif // PADDLE_ONLY_CPU
}
im2col
(
*
context
,
input
,
output_cfo
,
stride
,
stride
,
padding
,
padding
);
im2col_ocf
(
*
context
,
input
,
output_ocf
,
stride
,
stride
,
padding
,
padding
);
...
...
@@ -85,7 +85,8 @@ void testIm2col() {
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
out_cfo_ptr
=
output_cfo
.
data
<
float
>
();
}
else
{
output_tmp
.
CopyFrom
<
float
>
(
output_cfo
,
paddle
::
platform
::
CPUPlace
());
output_tmp
.
CopyFrom
<
float
>
(
output_cfo
,
paddle
::
platform
::
CPUPlace
(),
*
context
);
out_cfo_ptr
=
output_tmp
.
data
<
float
>
();
}
EXPECT_EQ
(
out_cfo_ptr
[
0
],
0
);
...
...
@@ -101,7 +102,8 @@ void testIm2col() {
if
(
paddle
::
platform
::
is_cpu_place
(
*
place
))
{
out_ocf_ptr
=
output_ocf
.
data
<
float
>
();
}
else
{
output_tmp
.
CopyFrom
<
float
>
(
output_ocf
,
paddle
::
platform
::
CPUPlace
());
output_tmp
.
CopyFrom
<
float
>
(
output_ocf
,
paddle
::
platform
::
CPUPlace
(),
*
context
);
out_ocf_ptr
=
output_tmp
.
data
<
float
>
();
}
EXPECT_EQ
(
out_ocf_ptr
[
0
],
0
);
...
...
paddle/operators/math/math_function_test.cc
浏览文件 @
458a2da3
...
...
@@ -17,17 +17,18 @@ TEST(math_function, notrans_mul_trans) {
auto
*
gpu_place
=
new
paddle
::
platform
::
GPUPlace
(
0
);
paddle
::
platform
::
CUDADeviceContext
context
(
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
);
input2_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
,
context
);
input2_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
,
context
);
out_gpu
.
mutable_data
<
float
>
({
2
,
2
},
*
gpu_place
);
paddle
::
operators
::
math
::
matmul
<
paddle
::
platform
::
GPUPlace
,
float
>
(
context
,
input1_gpu
,
false
,
input2_gpu
,
true
,
1
,
&
out_gpu
,
0
);
out
.
CopyFrom
<
float
>
(
out_gpu
,
*
cpu_place
);
out
.
CopyFrom
<
float
>
(
out_gpu
,
*
cpu_place
,
context
);
float
*
out_ptr
=
out
.
data
<
float
>
();
context
.
Wait
();
EXPECT_EQ
(
out_ptr
[
0
],
5
);
EXPECT_EQ
(
out_ptr
[
1
],
14
);
EXPECT_EQ
(
out_ptr
[
2
],
14
);
...
...
@@ -50,17 +51,18 @@ TEST(math_function, trans_mul_notrans) {
auto
*
gpu_place
=
new
paddle
::
platform
::
GPUPlace
(
0
);
paddle
::
platform
::
CUDADeviceContext
context
(
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
);
input2_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
,
context
);
input2_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
,
context
);
out_gpu
.
mutable_data
<
float
>
({
3
,
3
},
*
gpu_place
);
paddle
::
operators
::
math
::
matmul
<
paddle
::
platform
::
GPUPlace
,
float
>
(
context
,
input1_gpu
,
true
,
input2_gpu
,
false
,
1
,
&
out_gpu
,
0
);
out
.
CopyFrom
<
float
>
(
out_gpu
,
*
cpu_place
);
out
.
CopyFrom
<
float
>
(
out_gpu
,
*
cpu_place
,
context
);
float
*
out_ptr
=
out
.
data
<
float
>
();
context
.
Wait
();
EXPECT_EQ
(
out_ptr
[
0
],
9
);
EXPECT_EQ
(
out_ptr
[
1
],
12
);
EXPECT_EQ
(
out_ptr
[
2
],
15
);
...
...
@@ -98,9 +100,9 @@ TEST(math_function, gemm_notrans_cublas) {
auto
*
gpu_place
=
new
paddle
::
platform
::
GPUPlace
(
0
);
paddle
::
platform
::
CUDADeviceContext
context
(
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
);
input2_gpu
.
CopyFrom
<
float
>
(
input2
,
*
gpu_place
);
input3_gpu
.
CopyFrom
<
float
>
(
input3
,
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
,
context
);
input2_gpu
.
CopyFrom
<
float
>
(
input2
,
*
gpu_place
,
context
);
input3_gpu
.
CopyFrom
<
float
>
(
input3
,
*
gpu_place
,
context
);
float
*
a
=
input1_gpu
.
data
<
float
>
();
float
*
b
=
input2_gpu
.
data
<
float
>
();
float
*
c
=
input3_gpu
.
mutable_data
<
float
>
(
*
gpu_place
);
...
...
@@ -108,7 +110,7 @@ TEST(math_function, gemm_notrans_cublas) {
paddle
::
operators
::
math
::
gemm
<
paddle
::
platform
::
GPUPlace
,
float
>
(
context
,
false
,
false
,
m
,
n
,
k
,
1
,
a
,
3
,
b
+
1
,
4
,
1
,
c
+
1
,
4
);
input3
.
CopyFrom
<
float
>
(
input3_gpu
,
*
cpu_place
);
input3
.
CopyFrom
<
float
>
(
input3_gpu
,
*
cpu_place
,
context
);
// numpy code:
// a = np.arange(6).reshape(2, 3)
...
...
@@ -116,6 +118,7 @@ TEST(math_function, gemm_notrans_cublas) {
// c = np.arange(8).reshape(2, 4)[:, 1:]
// out = np.arange(8).reshape(2, 4)
// out[:, 1:] = np.dot(a, b) + c
context
.
Wait
();
EXPECT_EQ
(
input3_ptr
[
0
],
0
);
EXPECT_EQ
(
input3_ptr
[
1
],
24
);
EXPECT_EQ
(
input3_ptr
[
2
],
28
);
...
...
@@ -152,9 +155,9 @@ TEST(math_function, gemm_trans_cublas) {
auto
*
gpu_place
=
new
paddle
::
platform
::
GPUPlace
(
0
);
paddle
::
platform
::
CUDADeviceContext
context
(
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
);
input2_gpu
.
CopyFrom
<
float
>
(
input2
,
*
gpu_place
);
input3_gpu
.
CopyFrom
<
float
>
(
input3
,
*
gpu_place
);
input1_gpu
.
CopyFrom
<
float
>
(
input1
,
*
gpu_place
,
context
);
input2_gpu
.
CopyFrom
<
float
>
(
input2
,
*
gpu_place
,
context
);
input3_gpu
.
CopyFrom
<
float
>
(
input3
,
*
gpu_place
,
context
);
float
*
a
=
input1_gpu
.
data
<
float
>
();
float
*
b
=
input2_gpu
.
data
<
float
>
();
float
*
c
=
input3_gpu
.
mutable_data
<
float
>
(
*
gpu_place
);
...
...
@@ -162,7 +165,8 @@ TEST(math_function, gemm_trans_cublas) {
paddle
::
operators
::
math
::
gemm
<
paddle
::
platform
::
GPUPlace
,
float
>
(
context
,
false
,
true
,
m
,
n
,
k
,
1
,
a
,
3
,
b
+
3
,
3
,
1
,
c
+
1
,
4
);
input3
.
CopyFrom
<
float
>
(
input3_gpu
,
*
cpu_place
);
input3
.
CopyFrom
<
float
>
(
input3_gpu
,
*
cpu_place
,
context
);
context
.
Wait
();
EXPECT_EQ
(
input3_ptr
[
0
],
0
);
EXPECT_EQ
(
input3_ptr
[
1
],
24
);
...
...
paddle/operators/multiplex_op.cu
浏览文件 @
458a2da3
...
...
@@ -33,7 +33,8 @@ class MultiplexGPUKernel : public framework::OpKernel<T> {
auto
cols
=
ins
[
0
]
->
numel
()
/
rows
;
// copy index to cpu
Tensor
index_t_cpu
;
index_t_cpu
.
CopyFrom
<
int32_t
>
(
*
ids
,
platform
::
CPUPlace
());
index_t_cpu
.
CopyFrom
<
int32_t
>
(
*
ids
,
platform
::
CPUPlace
(),
ctx
.
device_context
());
auto
*
index
=
index_t_cpu
.
data
<
int32_t
>
();
auto
stream
=
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
ctx
.
device_context
())
...
...
@@ -70,7 +71,8 @@ class MultiplexGradGPUKernel : public framework::OpKernel<T> {
auto
cols
=
ins
[
0
]
->
numel
()
/
rows
;
// copy index to cpu
Tensor
index_t_cpu
;
index_t_cpu
.
CopyFrom
<
int32_t
>
(
*
ids
,
platform
::
CPUPlace
());
index_t_cpu
.
CopyFrom
<
int32_t
>
(
*
ids
,
platform
::
CPUPlace
(),
ctx
.
device_context
());
auto
*
index
=
index_t_cpu
.
data
<
int32_t
>
();
auto
stream
=
reinterpret_cast
<
const
platform
::
CUDADeviceContext
&>
(
...
...
paddle/operators/recurrent_op.cc
浏览文件 @
458a2da3
...
...
@@ -46,7 +46,7 @@ void RecurrentAlgorithm::Run(const Scope& scope,
}
(
*
stepnet_
)
->
Run
(
*
step_scopes
[
step_id
],
dev_ctx
);
}
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len
);
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len
,
dev_ctx
);
}
void
RecurrentAlgorithm
::
CreateScopes
(
const
Scope
&
scope
,
...
...
@@ -151,12 +151,12 @@ void RecurrentGradientAlgorithm::Run(
auto
&
step_scopes
=
GetStepScopes
(
scope
);
rnn
::
SegmentInputs
(
step_scopes
,
arg_
->
inlinks
,
seq_len
);
for
(
int
step_id
=
seq_len
-
1
;
step_id
>=
0
;
--
step_id
)
{
if
(
st
ep_id
!=
seq_len
-
1
)
{
if
(
st
atic_cast
<
size_t
>
(
step_id
)
!=
seq_len
-
1
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
1
);
}
(
*
stepnet_
)
->
Run
(
*
step_scopes
[
step_id
],
dev_ctx
);
}
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len
);
rnn
::
ConcatOutputs
(
step_scopes
,
arg_
->
outlinks
,
seq_len
,
dev_ctx
);
LinkBootMemoryGradients
(
step_scopes
[
0
]);
}
...
...
paddle/operators/reshape_op.h
浏览文件 @
458a2da3
...
...
@@ -33,7 +33,7 @@ class ReshapeKernel : public framework::OpKernel<T> {
std
::
transform
(
shape
.
begin
(),
shape
.
end
(),
shape_int64
.
begin
(),
[](
int
a
)
{
return
static_cast
<
int64_t
>
(
a
);
});
auto
out_dims
=
framework
::
make_ddim
(
shape_int64
);
out
->
CopyFrom
<
T
>
(
*
in
,
ctx
.
GetPlace
());
out
->
CopyFrom
<
T
>
(
*
in
,
ctx
.
GetPlace
()
,
ctx
.
device_context
()
);
out
->
Resize
(
out_dims
);
}
};
...
...
@@ -47,7 +47,7 @@ class ReshapeGradKernel : public framework::OpKernel<T> {
d_x
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
in_dims
=
d_x
->
dims
();
d_x
->
CopyFrom
<
T
>
(
*
d_out
,
ctx
.
GetPlace
());
d_x
->
CopyFrom
<
T
>
(
*
d_out
,
ctx
.
GetPlace
()
,
ctx
.
device_context
()
);
d_x
->
Resize
(
in_dims
);
}
};
...
...
paddle/operators/rnn/recurrent_op_utils.cc
浏览文件 @
458a2da3
...
...
@@ -51,7 +51,7 @@ void SegmentInputs(const std::vector<Scope*>& step_scopes,
void
ConcatOutputs
(
const
std
::
vector
<
Scope
*>&
step_scopes
,
const
std
::
vector
<
std
::
string
>&
outlinks
,
const
size_t
seq_len
)
{
const
size_t
seq_len
,
const
platform
::
DeviceContext
&
ctx
)
{
for
(
size_t
i
=
0
;
i
<
outlinks
.
size
();
i
++
)
{
auto
*
output_var
=
step_scopes
[
0
]
->
parent
().
FindVar
(
outlinks
[
i
]);
PADDLE_ENFORCE_NOT_NULL
(
output_var
,
"output link [%s] is not in scope."
,
...
...
@@ -72,7 +72,7 @@ void ConcatOutputs(const std::vector<Scope*>& step_scopes,
// TODO(luotao02) data type and platform::DeviceContext() should set
// correctly
(
output
->
Slice
<
float
>
(
j
,
j
+
1
))
.
CopyFrom
<
float
>
(
*
step_output
,
platform
::
CPUPlace
());
.
CopyFrom
<
float
>
(
*
step_output
,
platform
::
CPUPlace
()
,
ctx
);
}
}
}
...
...
paddle/operators/rnn/recurrent_op_utils.h
浏览文件 @
458a2da3
...
...
@@ -71,7 +71,7 @@ void SegmentInputs(const std::vector<Scope*>& step_scopes,
*/
void
ConcatOutputs
(
const
std
::
vector
<
Scope
*>&
step_scopes
,
const
std
::
vector
<
std
::
string
>&
outlinks
,
const
size_t
seq_len
);
const
size_t
seq_len
,
const
platform
::
DeviceContext
&
ctx
);
void
LinkMemories
(
const
std
::
vector
<
Scope
*>&
step_scopes
,
const
std
::
vector
<
MemoryAttr
>&
memories
,
const
size_t
step_id
,
...
...
paddle/operators/uniform_random_op.cc
浏览文件 @
458a2da3
...
...
@@ -54,7 +54,7 @@ class UniformRandomOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
->
Attrs
().
Get
<
float
>
(
"min"
)
<
ctx
->
Attrs
().
Get
<
float
>
(
"max"
),
"uniform_random's min must less then max"
);
auto
dims
=
Attr
<
std
::
vector
<
int
>>
(
"dims"
);
auto
&
dims
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"dims"
);
std
::
vector
<
int64_t
>
temp
;
temp
.
reserve
(
dims
.
size
());
for
(
auto
dim
:
dims
)
{
...
...
paddle/pybind/tensor_py.h
浏览文件 @
458a2da3
...
...
@@ -57,7 +57,18 @@ struct CastToPyBufferImpl<true, I, ARGS...> {
}
framework
::
Tensor
dst_tensor
;
if
(
paddle
::
platform
::
is_gpu_place
(
tensor
.
place
()))
{
dst_tensor
.
CopyFrom
<
CUR_TYPE
>
(
tensor
,
platform
::
CPUPlace
());
#ifdef PADDLE_WITH_CUDA
auto
*
src_ptr
=
static_cast
<
const
void
*>
(
tensor
.
data
<
CUR_TYPE
>
());
auto
*
dst_ptr
=
static_cast
<
void
*>
(
dst_tensor
.
mutable_data
<
CUR_TYPE
>
(
tensor
.
dims
(),
platform
::
CPUPlace
()));
// TODO(qijun): Here we use default CUDA stream to set GPU Tensor to
// a Python numpy array. It's better to manage CDUA stream unifiedly.
paddle
::
platform
::
GpuMemcpySync
(
dst_ptr
,
src_ptr
,
sizeof
(
CUR_TYPE
)
*
tensor
.
numel
(),
cudaMemcpyDeviceToHost
);
#else
PADDLE_THROW
(
"'GPUPlace' is not supported in CPU only device."
);
#endif
}
else
if
(
paddle
::
platform
::
is_cpu_place
(
tensor
.
place
()))
{
dst_tensor
=
tensor
;
}
...
...
@@ -120,6 +131,8 @@ void PyCUDATensorSetFromArray(
self
.
Resize
(
framework
::
make_ddim
(
dims
));
auto
*
dst
=
self
.
mutable_data
<
T
>
(
place
);
// TODO(qijun): Here we use default CUDA stream to set a Python numpy
// array to a GPU Tensor. It's better to manage CDUA stream unifiedly.
paddle
::
platform
::
GpuMemcpySync
(
dst
,
array
.
data
(),
sizeof
(
T
)
*
array
.
size
(),
cudaMemcpyHostToDevice
);
}
...
...
python/paddle/v2/framework/tests/test_activation_op.py
浏览文件 @
458a2da3
...
...
@@ -363,5 +363,26 @@ class TestSoftsign(OpTest):
self
.
check_grad
([
'X'
],
'Y'
,
max_relative_error
=
0.007
)
class
TestThresholdedRelu
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"thresholded_relu"
threshold
=
0.25
self
.
relative_error
=
0.005
X
=
np
.
random
.
uniform
(
-
1
,
1
,
[
11
,
17
]).
astype
(
"float32"
)
# Same reason as TestAbs
X
[
np
.
abs
(
X
-
threshold
)
<
self
.
relative_error
]
=
threshold
+
0.2
self
.
inputs
=
{
'X'
:
X
}
self
.
attrs
=
{
'threshold'
:
threshold
}
self
.
outputs
=
{
'Y'
:
(
X
>
threshold
)
*
X
}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
'X'
],
'Y'
,
max_relative_error
=
self
.
relative_error
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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