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PaddleDetection
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07923ba0
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PaddleDetection
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07923ba0
编写于
2月 12, 2018
作者:
D
dzhwinter
提交者:
GitHub
2月 12, 2018
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电子邮件补丁
差异文件
Memory/dropout4 (#8407)
* "merge random generator kernel and mul" * "fix dropout"
上级
91aac572
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
21 addition
and
21 deletion
+21
-21
paddle/fluid/operators/dropout_op.cu
paddle/fluid/operators/dropout_op.cu
+21
-21
未找到文件。
paddle/fluid/operators/dropout_op.cu
浏览文件 @
07923ba0
...
@@ -23,24 +23,23 @@ namespace paddle {
...
@@ -23,24 +23,23 @@ namespace paddle {
namespace
operators
{
namespace
operators
{
template
<
typename
T
,
typename
AttrType
>
template
<
typename
T
,
typename
AttrType
>
struct
MaskGenerator
{
__global__
void
RandomGenerator
(
const
size_t
n
,
const
int
seed
,
AttrType
dropout_prob
;
const
AttrType
dropout_prob
,
const
T
*
src
,
int
seed
;
T
*
mask_data
,
T
*
dst
)
{
thrust
::
minstd_rand
rng
;
rng
.
seed
(
seed
);
thrust
::
uniform_real_distribution
<
AttrType
>
dist
(
0
,
1
);
__host__
__device__
MaskGenerator
(
AttrType
dropout_prob
,
int
seed
)
int
idx
=
blockDim
.
x
*
blockIdx
.
x
+
threadIdx
.
x
;
:
dropout_prob
(
dropout_prob
),
seed
(
seed
)
{}
for
(;
idx
<
n
;
idx
+=
blockDim
.
x
*
gridDim
.
x
)
{
inline
__host__
__device__
T
operator
()(
const
unsigned
int
n
)
const
{
thrust
::
minstd_rand
rng
;
rng
.
seed
(
seed
);
thrust
::
uniform_real_distribution
<
AttrType
>
dist
(
0
,
1
);
rng
.
discard
(
n
);
if
(
dist
(
rng
)
<
dropout_prob
)
{
if
(
dist
(
rng
)
<
dropout_prob
)
{
return
static_cast
<
T
>
(
0
);
mask_data
[
idx
]
=
static_cast
<
T
>
(
0
);
}
else
{
mask_data
[
idx
]
=
static_cast
<
T
>
(
1
);
}
}
return
static_cast
<
T
>
(
1
)
;
dst
[
idx
]
=
mask_data
[
idx
]
*
src
[
idx
]
;
}
}
}
;
}
// It seems that Eigen::Tensor::setRandom in GPU will SEGFAULT.
// It seems that Eigen::Tensor::setRandom in GPU will SEGFAULT.
// Use std::random and thrust::random(thrust is a std library in CUDA) to
// Use std::random and thrust::random(thrust is a std library in CUDA) to
...
@@ -61,18 +60,19 @@ class GPUDropoutKernel : public framework::OpKernel<T> {
...
@@ -61,18 +60,19 @@ class GPUDropoutKernel : public framework::OpKernel<T> {
if
(
!
context
.
Attr
<
bool
>
(
"is_test"
))
{
if
(
!
context
.
Attr
<
bool
>
(
"is_test"
))
{
auto
*
mask
=
context
.
Output
<
Tensor
>
(
"Mask"
);
auto
*
mask
=
context
.
Output
<
Tensor
>
(
"Mask"
);
auto
*
mask_data
=
mask
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
*
mask_data
=
mask
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
size
=
framework
::
product
(
mask
->
dims
());
size_t
size
=
framework
::
product
(
mask
->
dims
());
auto
*
x_data
=
x
->
data
<
T
>
();
auto
*
y_data
=
y
->
mutable_data
<
T
>
(
context
.
GetPlace
());
std
::
random_device
rnd
;
std
::
random_device
rnd
;
int
seed
=
int
seed
=
context
.
Attr
<
bool
>
(
"fix_seed"
)
?
context
.
Attr
<
int
>
(
"seed"
)
:
rnd
();
context
.
Attr
<
bool
>
(
"fix_seed"
)
?
context
.
Attr
<
int
>
(
"seed"
)
:
rnd
();
thrust
::
counting_iterator
<
unsigned
int
>
index_sequence_begin
(
0
);
int
threads
=
512
;
thrust
::
transform
(
index_sequence_begin
,
index_sequence_begin
+
size
,
int
grid
=
(
x
->
numel
()
+
threads
-
1
)
/
threads
;
thrust
::
device_ptr
<
T
>
(
mask_data
),
RandomGenerator
<
T
,
AttrType
><<<
grid
,
threads
,
0
,
MaskGenerator
<
T
,
AttrType
>
(
dropout_prob
,
seed
));
context
.
cuda_device_context
().
stream
()
>>>
(
auto
M
=
EigenMatrix
<
T
>::
Reshape
(
*
mask
,
1
);
size
,
seed
,
dropout_prob
,
x_data
,
mask_data
,
y_data
);
Y
.
device
(
place
)
=
X
*
M
;
}
else
{
}
else
{
Y
.
device
(
place
)
=
X
*
(
1.0
f
-
dropout_prob
);
Y
.
device
(
place
)
=
X
*
(
1.0
f
-
dropout_prob
);
}
}
...
...
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