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体验新版 GitCode,发现更多精彩内容 >>
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fcff9758
编写于
1月 29, 2018
作者:
Y
Yibing Liu
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电子邮件补丁
差异文件
Add label smooth operator
上级
a585b585
变更
4
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Showing
4 changed file
with
210 addition
and
0 deletion
+210
-0
paddle/operators/label_smooth_op.cc
paddle/operators/label_smooth_op.cc
+85
-0
paddle/operators/label_smooth_op.cu
paddle/operators/label_smooth_op.cu
+26
-0
paddle/operators/label_smooth_op.h
paddle/operators/label_smooth_op.h
+58
-0
python/paddle/v2/fluid/tests/test_label_smooth_op.py
python/paddle/v2/fluid/tests/test_label_smooth_op.py
+41
-0
未找到文件。
paddle/operators/label_smooth_op.cc
0 → 100644
浏览文件 @
fcff9758
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/operators/label_smooth_op.h"
namespace
paddle
{
namespace
operators
{
class
LabelSmoothOp
:
public
framework
::
OperatorWithKernel
{
public:
LabelSmoothOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorWithKernel
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of LabelSmoothOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of LabelSmoothOp should not be null."
);
auto
in_dims
=
ctx
->
GetInputDim
(
"X"
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
ctx
->
SetOutputDim
(
"Out"
,
in_dims
);
}
};
class
LabelSmoothOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
LabelSmoothOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"The input label of LabelSmooth operator."
);
AddOutput
(
"Out"
,
"The smoothed label of LabelSmooth operator."
);
AddAttr
<
float
>
(
"epsilon"
,
"(float, default 0.0f)"
"The smoothing parameter of LabelSmooth operator."
)
.
SetDefault
(
0.0
f
);
AddComment
(
R"DOC(
LabelSmooth Operator.
)DOC"
);
}
};
class
LabelSmoothGradOp
:
public
framework
::
OperatorWithKernel
{
public:
LabelSmoothGradOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorWithKernel
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) shouldn't be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) shouldn't be null."
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
label_smooth
,
ops
::
LabelSmoothOp
,
ops
::
LabelSmoothOpMaker
,
label_smooth_grad
,
ops
::
LabelSmoothGradOp
);
REGISTER_OP_CPU_KERNEL
(
label_smooth
,
ops
::
LabelSmoothKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
LabelSmoothKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
label_smooth_grad
,
ops
::
LabelSmoothGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
LabelSmoothGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
paddle/operators/label_smooth_op.cu
0 → 100644
浏览文件 @
fcff9758
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/operators/label_smooth_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
label_smooth
,
ops
::
LabelSmoothKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
LabelSmoothKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
label_smooth_grad
,
ops
::
LabelSmoothGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
LabelSmoothGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
paddle/operators/label_smooth_op.h
0 → 100644
浏览文件 @
fcff9758
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 "paddle/framework/eigen.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
DeviceContext
,
typename
T
>
class
LabelSmoothKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
out_t
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
auto
*
in_t
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
);
auto
label_dim
=
in_t
->
dims
()[
1
];
out_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
epsilon
=
ctx
.
Attr
<
float
>
(
"epsilon"
);
auto
out
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
out_t
);
auto
in
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
in_t
);
auto
&
dev
=
*
ctx
.
template
device_context
<
DeviceContext
>().
eigen_device
();
out
.
device
(
dev
)
=
static_cast
<
T
>
(
1
-
epsilon
)
*
in
+
static_cast
<
T
>
(
epsilon
/
label_dim
);
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
LabelSmoothGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
d_out_t
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_in_t
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
d_in_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
d_out
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
d_out_t
);
auto
d_in
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
d_in_t
);
auto
epsilon
=
ctx
.
Attr
<
float
>
(
"epsilon"
);
auto
&
dev
=
*
ctx
.
template
device_context
<
DeviceContext
>().
eigen_device
();
d_in
.
device
(
dev
)
=
static_cast
<
T
>
(
1
-
epsilon
)
*
d_out
;
}
};
}
// namespace operators
}
// namespace paddle
python/paddle/v2/fluid/tests/test_label_smooth_op.py
0 → 100644
浏览文件 @
fcff9758
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
#
# 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.
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
class
TestLabelSmoothOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"label_smooth"
epsilon
=
0.1
batch_size
,
label_dim
=
5
,
10
label
=
np
.
zeros
((
batch_size
,
label_dim
)).
astype
(
"float64"
)
nonzero_index
=
np
.
random
.
randint
(
label_dim
,
size
=
(
batch_size
))
label
[
np
.
arange
(
batch_size
),
nonzero_index
]
=
1
smoothed_label
=
(
1
-
epsilon
)
*
label
+
epsilon
/
label_dim
self
.
inputs
=
{
'X'
:
label
}
self
.
attrs
=
{
'epsilon'
:
epsilon
}
self
.
outputs
=
{
'Out'
:
smoothed_label
}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
"X"
],
"Out"
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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