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d736fc0e
编写于
9月 13, 2017
作者:
Q
qijun
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add activation macro
上级
3c49e7b1
变更
10
隐藏空白更改
内联
并排
Showing
10 changed file
with
342 addition
and
87 deletion
+342
-87
paddle/framework/operator.h
paddle/framework/operator.h
+3
-3
paddle/operators/activation_op.cc
paddle/operators/activation_op.cc
+115
-0
paddle/operators/activation_op.cu
paddle/operators/activation_op.cu
+10
-1
paddle/operators/activation_op.h
paddle/operators/activation_op.h
+71
-0
paddle/operators/math/activation.h
paddle/operators/math/activation.h
+0
-20
paddle/operators/math/activation_functor.h
paddle/operators/math/activation_functor.h
+96
-0
paddle/operators/sigmoid_op.h
paddle/operators/sigmoid_op.h
+0
-62
paddle/pybind/pybind.cc
paddle/pybind/pybind.cc
+3
-1
python/paddle/v2/framework/tests/test_exp_op.py
python/paddle/v2/framework/tests/test_exp_op.py
+22
-0
python/paddle/v2/framework/tests/test_relu_op.py
python/paddle/v2/framework/tests/test_relu_op.py
+22
-0
未找到文件。
paddle/framework/operator.h
浏览文件 @
d736fc0e
...
...
@@ -139,9 +139,9 @@ class OperatorBase {
// Macro for define a clone method.
// If you are writing an kernel operator, `Clone` will be defined when you
// register it. i.e. `Clone` method is not needed to define by yourself.
#define DEFINE_OP_CLONE_METHOD(cls) \
std::unique_ptr<OperatorBase> Clone() const final { \
return std::unique_ptr<OperatorBase>(new cls(*this)); \
#define DEFINE_OP_CLONE_METHOD(cls)
\
std::unique_ptr<
::paddle::framework::
OperatorBase> Clone() const final { \
return std::unique_ptr<
::paddle::framework::
OperatorBase>(new cls(*this)); \
}
// Macro for define a default constructor for Operator.
...
...
paddle/operators/
sigmoid
_op.cc
→
paddle/operators/
activation
_op.cc
浏览文件 @
d736fc0e
...
...
@@ -12,19 +12,33 @@
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/sigmoid_op.h"
#include "paddle/operators/activation_op.h"
#define FILL_ACTIVATION_OP \
public: \
using framework::OperatorWithKernel::OperatorWithKernel; \
\
protected: \
void InferShape(const framework::InferShapeContext &ctx) const override { \
ctx.Output<framework::Tensor>("Y")->Resize( \
ctx.Input<framework::Tensor>("X")->dims()); \
}
#define FILL_ACTIVATION_GRAD_OP \
public: \
using framework::OperatorWithKernel::OperatorWithKernel; \
\
protected: \
void InferShape(const framework::InferShapeContext &ctx) const override { \
ctx.Output<framework::Tensor>(framework::GradVarName("X")) \
->Resize(ctx.Input<framework::Tensor>("Y")->dims()); \
}
namespace
paddle
{
namespace
operators
{
class
SigmoidOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
ctx
.
Output
<
Tensor
>
(
"Y"
)
->
Resize
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
());
}
FILL_ACTIVATION_OP
};
class
SigmoidOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -32,23 +46,52 @@ class SigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
SigmoidOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"
sigmoid input
"
);
AddOutput
(
"Y"
,
"
sigmoid output
"
);
AddComment
(
"Sigmoid
function
"
);
AddInput
(
"X"
,
"
Input of Sigmoid operator
"
);
AddOutput
(
"Y"
,
"
Output of Sigmoid operator
"
);
AddComment
(
"Sigmoid
activation operator
"
);
}
};
class
SigmoidOpGrad
:
public
framework
::
OperatorWithKernel
{
FILL_ACTIVATION_GRAD_OP
};
class
ExpOp
:
public
framework
::
OperatorWithKernel
{
FILL_ACTIVATION_OP
};
class
ExpOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
ExpOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Exp operator"
);
AddOutput
(
"Y"
,
"Output of Exp operator"
);
AddComment
(
"Exp activation operator"
);
}
};
class
ExpOpGrad
:
public
framework
::
OperatorWithKernel
{
FILL_ACTIVATION_GRAD_OP
};
class
ReluOp
:
public
framework
::
OperatorWithKernel
{
FILL_ACTIVATION_OP
};
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
))
->
Resize
(
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
());
class
ReluOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ReluOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"Input of Relu operator"
);
AddOutput
(
"Y"
,
"Output of Relu operator"
);
AddComment
(
"Relu activation operator"
);
}
};
class
ReluOpGrad
:
public
framework
::
OperatorWithKernel
{
FILL_ACTIVATION_GRAD_OP
};
}
// namespace operators
}
// namespace paddle
...
...
@@ -59,3 +102,14 @@ REGISTER_OP_CPU_KERNEL(sigmoid,
ops
::
SigmoidKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
sigmoid_grad
,
ops
::
SigmoidGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP
(
exp
,
ops
::
ExpOp
,
ops
::
ExpOpMaker
,
exp_grad
,
ops
::
ExpOpGrad
);
REGISTER_OP_CPU_KERNEL
(
exp
,
ops
::
ExpKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
exp_grad
,
ops
::
ExpGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP
(
relu
,
ops
::
ReluOp
,
ops
::
ReluOpMaker
,
relu_grad
,
ops
::
ReluOpGrad
);
REGISTER_OP_CPU_KERNEL
(
relu
,
ops
::
ReluKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
relu_grad
,
ops
::
ReluGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
paddle/operators/
sigmoid
_op.cu
→
paddle/operators/
activation
_op.cu
浏览文件 @
d736fc0e
...
...
@@ -13,7 +13,7 @@
limitations under the License. */
#define EIGEN_USE_GPU
#include "paddle/operators/
sigmoid
_op.h"
#include "paddle/operators/
activation
_op.h"
namespace
ops
=
paddle
::
operators
;
...
...
@@ -21,3 +21,12 @@ REGISTER_OP_GPU_KERNEL(sigmoid,
ops
::
SigmoidKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
sigmoid_grad
,
ops
::
SigmoidGradKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
exp
,
ops
::
ExpKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
exp_grad
,
ops
::
ExpGradKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
relu
,
ops
::
ReluKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
relu_grad
,
ops
::
ReluGradKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
paddle/operators/activation_op.h
0 → 100644
浏览文件 @
d736fc0e
/* 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"
#include "paddle/operators/math/activation_functor.h"
#define ACTIVATION_KERNEL_NAME(ACTIVATION_NAME) ACTIVATION_NAME##Kernel
#define DEFINE_ACTIVATION_KERNEL(ACTIVATION_NAME) \
template <typename Place, typename T> \
class ACTIVATION_KERNEL_NAME(ACTIVATION_NAME) : public framework::OpKernel { \
public: \
void Compute(const framework::ExecutionContext& context) const override { \
auto* X = context.Input<framework::Tensor>("X"); \
auto* Y = context.Output<framework::Tensor>("Y"); \
Y->mutable_data<T>(context.GetPlace()); \
math::ACTIVATION_NAME<Place, T> functor; \
auto* device_context = context.device_context(); \
functor(*device_context, *X, Y); \
} \
};
#define DEFINE_ACTIVATION_GRAD_KERNEL(ACTIVATION_GRAD_NAME) \
template <typename Place, typename T> \
class ACTIVATION_KERNEL_NAME(ACTIVATION_GRAD_NAME) \
: public framework::OpKernel { \
public: \
void Compute(const framework::ExecutionContext& context) const override { \
auto* X = context.Input<framework::Tensor>("X"); \
auto* Y = context.Input<framework::Tensor>("Y"); \
auto* dY = \
context.Input<framework::Tensor>(framework::GradVarName("Y")); \
auto* dX = \
context.Output<framework::Tensor>(framework::GradVarName("X")); \
dX->mutable_data<T>(context.GetPlace()); \
math::ACTIVATION_GRAD_NAME<Place, T> functor; \
auto* device_context = context.device_context(); \
functor(*device_context, *X, *Y, *dY, dX); \
} \
};
namespace
paddle
{
namespace
operators
{
DEFINE_ACTIVATION_KERNEL
(
Sigmoid
);
DEFINE_ACTIVATION_GRAD_KERNEL
(
SigmoidGrad
);
DEFINE_ACTIVATION_KERNEL
(
Exp
);
DEFINE_ACTIVATION_GRAD_KERNEL
(
ExpGrad
);
DEFINE_ACTIVATION_KERNEL
(
Relu
);
DEFINE_ACTIVATION_GRAD_KERNEL
(
ReluGrad
);
}
// namespace operators
}
// namespace paddle
paddle/operators/math/activation.h
已删除
100644 → 0
浏览文件 @
3c49e7b1
#include "paddle/framework/eigen.h"
#include "paddle/framework/tensor.h"
namespace
paddle
{
namespace
operators
{
namespace
math
{
template
<
typename
Place
,
typename
T
>
struct
sigmoid
{
void
operator
()(
const
platform
::
DeviceContext
&
deice_context
,
const
framework
::
Tensor
&
input
,
framework
::
Tensor
*
output
)
{
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
output
);
auto
y
=
framework
::
EigenVector
<
T
>::
Flatten
(
input
);
auto
*
place
=
device_context
.
get_eigen_device
<
Place
>
();
y
.
device
(
*
place
)
=
1.
/
(
1.
+
(
-
x
).
exp
());
}
};
}
}
}
paddle/operators/math/activation_functor.h
0 → 100644
浏览文件 @
d736fc0e
/* 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/tensor.h"
namespace
paddle
{
namespace
operators
{
namespace
math
{
template
<
typename
Place
,
typename
T
>
struct
Sigmoid
{
void
operator
()(
const
platform
::
DeviceContext
&
device_context
,
const
framework
::
Tensor
&
X
,
framework
::
Tensor
*
Y
)
{
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
X
);
auto
y
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
Y
);
auto
*
place
=
device_context
.
template
get_eigen_device
<
Place
>();
y
.
device
(
*
place
)
=
1.
/
(
1.
+
(
-
x
).
exp
());
}
};
template
<
typename
Place
,
typename
T
>
struct
SigmoidGrad
{
void
operator
()(
const
platform
::
DeviceContext
&
device_context
,
const
framework
::
Tensor
&
X
,
const
framework
::
Tensor
&
Y
,
const
framework
::
Tensor
&
dY
,
framework
::
Tensor
*
dX
)
{
auto
dx
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
auto
y
=
framework
::
EigenVector
<
T
>::
Flatten
(
Y
);
auto
dy
=
framework
::
EigenVector
<
T
>::
Flatten
(
dY
);
auto
*
place
=
device_context
.
template
get_eigen_device
<
Place
>();
dx
.
device
(
*
place
)
=
dy
*
y
*
(
1.
-
y
);
}
};
template
<
typename
Place
,
typename
T
>
struct
Exp
{
void
operator
()(
const
platform
::
DeviceContext
&
device_context
,
const
framework
::
Tensor
&
input
,
framework
::
Tensor
*
output
)
{
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
input
);
auto
y
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
output
);
auto
*
place
=
device_context
.
template
get_eigen_device
<
Place
>();
y
.
device
(
*
place
)
=
x
.
exp
();
}
};
template
<
typename
Place
,
typename
T
>
struct
ExpGrad
{
void
operator
()(
const
platform
::
DeviceContext
&
device_context
,
const
framework
::
Tensor
&
X
,
const
framework
::
Tensor
&
Y
,
const
framework
::
Tensor
&
dY
,
framework
::
Tensor
*
dX
)
{
auto
dx
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
auto
dy
=
framework
::
EigenVector
<
T
>::
Flatten
(
dY
);
auto
*
place
=
device_context
.
template
get_eigen_device
<
Place
>();
dx
.
device
(
*
place
)
=
dy
.
exp
();
}
};
template
<
typename
Place
,
typename
T
>
struct
Relu
{
void
operator
()(
const
platform
::
DeviceContext
&
device_context
,
const
framework
::
Tensor
&
input
,
framework
::
Tensor
*
output
)
{
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
input
);
auto
y
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
output
);
auto
*
place
=
device_context
.
template
get_eigen_device
<
Place
>();
y
.
device
(
*
place
)
=
x
.
cwiseMax
(
static_cast
<
T
>
(
0
));
}
};
template
<
typename
Place
,
typename
T
>
struct
ReluGrad
{
void
operator
()(
const
platform
::
DeviceContext
&
device_context
,
const
framework
::
Tensor
&
X
,
const
framework
::
Tensor
&
Y
,
const
framework
::
Tensor
&
dY
,
framework
::
Tensor
*
dX
)
{
auto
dx
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
auto
dy
=
framework
::
EigenVector
<
T
>::
Flatten
(
dY
);
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
X
);
auto
*
place
=
device_context
.
template
get_eigen_device
<
Place
>();
dx
.
device
(
*
place
)
=
dy
*
(
x
>
static_cast
<
T
>
(
0
)).
template
cast
<
T
>();
}
};
}
// namespace math
}
// namespace operators
}
// namespace paddle
paddle/operators/sigmoid_op.h
已删除
100644 → 0
浏览文件 @
3c49e7b1
/* 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
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenVector
=
framework
::
EigenVector
<
T
,
MajorType
,
IndexType
>
;
template
<
typename
Place
,
typename
T
>
class
SigmoidKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
input
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
output
=
context
.
Output
<
Tensor
>
(
"Y"
);
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
// The clipping is used in Paddle's raw implenmention
auto
X
=
EigenVector
<
T
>::
Flatten
(
*
input
);
auto
Y
=
EigenVector
<
T
>::
Flatten
(
*
output
);
auto
place
=
context
.
GetEigenDevice
<
Place
>
();
Y
.
device
(
place
)
=
1.
/
(
1.
+
(
-
X
).
exp
());
}
};
template
<
typename
Place
,
typename
T
>
class
SigmoidGradKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
Y_t
=
context
.
Input
<
Tensor
>
(
"Y"
);
auto
dY_t
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
dX_t
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
dX_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dX
=
EigenVector
<
T
>::
Flatten
(
*
dX_t
);
auto
Y
=
EigenVector
<
T
>::
Flatten
(
*
Y_t
);
auto
dY
=
EigenVector
<
T
>::
Flatten
(
*
dY_t
);
dX
.
device
(
context
.
GetEigenDevice
<
Place
>
())
=
dY
*
Y
*
(
1.
-
Y
);
}
};
}
// namespace operators
}
// namespace paddle
paddle/pybind/pybind.cc
浏览文件 @
d736fc0e
...
...
@@ -36,7 +36,6 @@ USE_OP(onehot_cross_entropy);
USE_OP
(
sgd
);
USE_OP
(
mul
);
USE_OP
(
mean
);
USE_OP
(
sigmoid
);
USE_OP
(
softmax
);
USE_OP
(
rowwise_add
);
USE_OP
(
fill_zeros_like
);
...
...
@@ -55,6 +54,9 @@ USE_OP(top_k);
USE_OP
(
squared_l2_distance
);
USE_OP
(
sum
);
USE_OP
(
reshape
);
USE_OP
(
sigmoid
);
USE_OP
(
exp
);
USE_OP
(
relu
);
namespace
paddle
{
namespace
framework
{
...
...
python/paddle/v2/framework/tests/test_exp_op.py
0 → 100644
浏览文件 @
d736fc0e
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
class
TestExp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"exp"
self
.
inputs
=
{
'X'
:
np
.
random
.
uniform
(
0.1
,
1
,
[
11
,
17
]).
astype
(
"float32"
)
}
self
.
outputs
=
{
'Y'
:
np
.
exp
(
self
.
inputs
[
'X'
])}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
"X"
],
"Y"
,
max_relative_error
=
0.007
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/v2/framework/tests/test_relu_op.py
0 → 100644
浏览文件 @
d736fc0e
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
class
TestExp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"exp"
self
.
inputs
=
{
'X'
:
np
.
random
.
uniform
(
-
1
,
1
,
[
11
,
17
]).
astype
(
"float32"
)
}
self
.
outputs
=
{
'Y'
:
np
.
maximum
(
self
.
inputs
[
'X'
],
0
)}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
"X"
],
"Y"
,
max_relative_error
=
0.007
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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