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体验新版 GitCode,发现更多精彩内容 >>
提交
60dda7bf
编写于
8月 15, 2018
作者:
T
tangwei12
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电子邮件补丁
差异文件
add gpu Implementation
上级
4661f558
变更
2
隐藏空白更改
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Showing
2 changed file
with
89 addition
and
2 deletion
+89
-2
paddle/fluid/operators/sampling_id_op.cc
paddle/fluid/operators/sampling_id_op.cc
+2
-2
paddle/fluid/operators/sampling_id_op.cu
paddle/fluid/operators/sampling_id_op.cu
+87
-0
未找到文件。
paddle/fluid/operators/sampling_id_op.cc
浏览文件 @
60dda7bf
...
...
@@ -25,7 +25,7 @@ namespace operators {
using
Tensor
=
framework
::
Tensor
;
template
<
typename
DeviceContext
,
typename
T
>
template
<
typename
T
>
class
SamplingIdKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
...
...
@@ -48,7 +48,7 @@ class SamplingIdKernel : public framework::OpKernel<T> {
std
::
vector
<
T
>
ids
(
batch_size
);
for
(
size_t
i
=
0
;
i
<
batch_size
;
++
i
)
{
double
r
=
dist
(
engine
);
T
r
=
dist
(
engine
);
int
idx
=
width
-
1
;
for
(
int
j
=
0
;
j
<
width
;
++
j
)
{
if
((
r
-=
ins_vector
[
i
*
width
+
j
])
<
0
)
{
...
...
paddle/fluid/operators/sampling_id_op.cu
0 → 100644
浏览文件 @
60dda7bf
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <thrust/random.h>
#include <thrust/transform.h>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
template
<
typename
T
>
struct
UniformGenerator
{
T
min_
,
max_
;
unsigned
int
seed_
;
__host__
__device__
UniformGenerator
(
T
min
,
T
max
,
int
seed
)
:
min_
(
min
),
max_
(
max
),
seed_
(
seed
)
{}
__host__
__device__
T
operator
()(
const
unsigned
int
n
)
const
{
thrust
::
minstd_rand
rng
;
rng
.
seed
(
seed_
);
thrust
::
uniform_real_distribution
<
T
>
dist
(
min_
,
max_
);
rng
.
discard
(
n
);
return
dist
(
rng
);
}
};
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
>
class
SamplingIdKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
const
Tensor
*
input
=
context
.
Input
<
Tensor
>
(
"X"
);
const
int
batch_size
=
static_cast
<
int
>
(
input
->
dims
()[
0
]);
const
int
width
=
static_cast
<
int
>
(
input
->
dims
()[
1
]);
std
::
vector
<
T
>
ins_vector
;
framework
::
TensorToVector
(
*
input
,
context
.
device_context
(),
&
ins_vector
);
unsigned
int
seed
=
static_cast
<
unsigned
int
>
(
context
.
Attr
<
int
>
(
"seed"
));
if
(
seed
==
0
)
{
std
::
random_device
rd
;
seed
=
rd
();
}
T
min
=
static_cast
<
T
>
(
context
.
Attr
<
float
>
(
"min"
));
T
max
=
static_cast
<
T
>
(
context
.
Attr
<
float
>
(
"max"
));
std
::
vector
<
T
>
ids
(
batch_size
);
for
(
size_t
i
=
0
;
i
<
batch_size
;
++
i
)
{
T
r
=
UniformGenerator
<
T
>
(
min
,
max
,
seed
);
int
idx
=
width
-
1
;
for
(
int
j
=
0
;
j
<
width
;
++
j
)
{
if
((
r
-=
ins_vector
[
i
*
width
+
j
])
<
0
)
{
idx
=
j
;
break
;
}
}
ids
[
i
]
=
ins_vector
[
i
*
width
+
idx
];
}
std
::
vector
<
int64_t
>
out_dim
;
out_dim
.
push_back
(
static_cast
<
int64_t
>
(
batch_size
));
Tensor
*
output
=
context
.
Output
<
Tensor
>
(
"Out"
);
output
->
Resize
(
framework
::
make_ddim
(
out_dim
));
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
framework
::
TensorFromVector
(
ids
,
context
.
device_context
(),
output
);
}
};
}
// namespace operators
}
// namespace paddle
REGISTER_OP_CPU_KERNEL
(
sampling_id
,
paddle
::
operators
::
SamplingIdKernel
<
float
>
,
paddle
::
operators
::
SamplingIdKernel
<
double
>
);
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