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e0ab2f71
编写于
8月 05, 2018
作者:
T
tangwei12
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电子邮件补丁
差异文件
new sampling op
上级
0964de11
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3
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3 changed file
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172 addition
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+172
-0
paddle/fluid/operators/sampling_id_op.cc
paddle/fluid/operators/sampling_id_op.cc
+64
-0
paddle/fluid/operators/sampling_id_op.cu
paddle/fluid/operators/sampling_id_op.cu
+40
-0
paddle/fluid/operators/sampling_id_op.h
paddle/fluid/operators/sampling_id_op.h
+68
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未找到文件。
paddle/fluid/operators/sampling_id_op.cc
0 → 100644
浏览文件 @
e0ab2f71
/* 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 "paddle/fluid/operators/sampling_id_op.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
class
SamplingIdOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of RowConvOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of RowConvOp should not be null."
);
auto
input_dims
=
ctx
->
GetInputDim
(
"X"
);
framework
::
DDim
dims
=
input_dims
;
ctx
->
SetOutputDim
(
"Out"
,
dims
);
ctx
->
ShareLoD
(
"X"
,
"Out"
);
}
};
class
SamplingIdOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"The input tensor of softmax. "
"2-D with shape [batch_size, input_feature_dimensions]."
);
AddOutput
(
"Out"
,
"Sliced data tensor."
);
AddComment
(
R"DOC(
SamplingId Operator.
@brief A layer for sampling id from multinomial distribution from the
input layer. Sampling one id for one sample. The result is stored in
output_.ids.
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
slice
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CUDADeviceContext
,
int
>
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CUDADeviceContext
,
int64_t
>
);
paddle/fluid/operators/sampling_id_op.cu
0 → 100644
浏览文件 @
e0ab2f71
/* 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 <algorithm>
#include <vector>
#include "paddle/fluid/operators/sampling_id_op.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
class
SamplingIdOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{}
}
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
samplingid
,
ops
::
SamplingIdOp
,
ops
::
SamplingIdOpMaker
,
paddle
::
framework
::
EmptyGradOpMaker
);
REGISTER_OP_CPU_KERNEL
(
slice
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
>
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int64_t
>
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
SamplingIdKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
paddle/fluid/operators/sampling_id_op.h
0 → 100644
浏览文件 @
e0ab2f71
/* Copyright (c) 2016 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. */
#pragma once
#include <random>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
DeviceContext
,
typename
T
>
class
SamplingIdKernel
:
public
framework
::
OpKernel
<
T
>
{
/// Produces random floating-point values, uniformly distributed on [0, 1).
std
::
uniform_real_distribution
<
double
>
rand1_
;
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
<
int
>
ids
(
batchSize
);
auto
&
reng
=
get
();
for
(
size_t
i
=
0
;
i
<
batchSize
;
++
i
)
{
double
r
=
rand1_
(
reng
);
int
id
=
dim
-
1
;
for
(
int
j
=
0
;
j
<
dim
;
++
j
)
{
if
((
r
-=
buf
[
i
*
dim
+
j
])
<
0
)
{
id
=
j
;
break
;
}
}
ids
[
i
]
=
id
;
}
std
::
vector
<
int64_t
>
out_dim
;
out_dim
.
push_back
(
static_cast
<
int64_t
>
(
batch_size
));
Tensor
*
output
=
context
.
Output
<
Tensor
>
(
"Output"
);
output
->
Resize
(
framework
::
make_ddim
(
in_dim
));
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
framework
::
TensorFromVector
(
ids
,
context
.
device_context
(),
output
);
}
std
::
default_random_engine
&
get
()
{
auto
engine
=
new
std
::
default_random_engine
;
engine
->
seed
(
defaultSeed
);
return
*
engine
;
}
private:
unsigned
int
defaultSeed
=
0
;
}
}
// namespace operators
}
// namespace paddle
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