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d28b3094
编写于
10月 02, 2017
作者:
S
sidgoyal78
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差异文件
Add momentum operator
上级
42e7fe05
变更
4
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4 changed file
with
197 addition
and
0 deletion
+197
-0
paddle/operators/momentum_op.cc
paddle/operators/momentum_op.cc
+89
-0
paddle/operators/momentum_op.cu
paddle/operators/momentum_op.cu
+20
-0
paddle/operators/momentum_op.h
paddle/operators/momentum_op.h
+53
-0
python/paddle/v2/framework/tests/test_momentum_op.py
python/paddle/v2/framework/tests/test_momentum_op.py
+35
-0
未找到文件。
paddle/operators/momentum_op.cc
0 → 100644
浏览文件 @
d28b3094
/* 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/momentum_op.h"
namespace
paddle
{
namespace
operators
{
class
MomentumOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
framework
::
InferShapeContextBase
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Param"
),
"Input(param) of Momentum should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Grad"
),
"Input(grad) of Momentum should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Velocity"
),
"Input(velocity) of Momentum should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"LearningRate"
),
"Input(LearningRate) of Momentum should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"ParamOut"
),
"Output(ParamOut) of Momentum should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"VelocityOut"
),
"Output(VelocityOut) of Momentum should not be null."
);
auto
param_dim
=
ctx
->
GetInputDim
(
"Param"
);
PADDLE_ENFORCE_EQ
(
param_dim
,
ctx
->
GetInputDim
(
"Grad"
),
"Param and Grad input of MomentumOp should have the same dimension."
);
PADDLE_ENFORCE_EQ
(
param_dim
,
ctx
->
GetInputDim
(
"Velocity"
),
"Param and Velocity of MomentumOp should have the same dimension."
);
PADDLE_ENFORCE_EQ
(
framework
::
product
(
ctx
->
GetInputDim
(
"LearningRate"
)),
1
,
"Learning_rate should be a scalar"
);
ctx
->
SetOutputDim
(
"ParamOut"
,
param_dim
);
ctx
->
SetOutputDim
(
"VelocityOut"
,
param_dim
);
}
};
class
MomentumOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
MomentumOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"Param"
,
"Input parameter"
);
AddInput
(
"Grad"
,
"Input gradient"
);
AddInput
(
"Velocity"
,
"Input velocity"
);
AddInput
(
"LearningRate"
,
"Input learning rate"
);
AddOutput
(
"ParamOut"
,
"Output parameter"
);
AddOutput
(
"VelocityOut"
,
"Output velocity"
);
AddAttr
<
float
>
(
"mu"
,
"Momentum coefficient"
);
AddComment
(
R"DOC(
Momentum Algorithm (momentum).
velocity_out = mu * velocity - learning_rate * grad
param_out = param + velocity_out
Ref: Sutskever, Ilya, et al. "On the importance of initialization
and momentum in deep learning." ICML 2013;
http://jmlr.org/proceedings/papers/v28/sutskever13.pdf
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_WITHOUT_GRADIENT
(
momentum
,
ops
::
MomentumOp
,
ops
::
MomentumOpMaker
);
REGISTER_OP_CPU_KERNEL
(
momentum
,
ops
::
MomentumOpKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
paddle/operators/momentum_op.cu
0 → 100644
浏览文件 @
d28b3094
/* 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. */
#define EIGEN_USE_GPU
#include "paddle/operators/momentum_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_GPU_KERNEL
(
momentum
,
ops
::
MomentumOpKernel
<
paddle
::
platform
::
GPUPlace
,
float
>
);
paddle/operators/momentum_op.h
0 → 100644
浏览文件 @
d28b3094
/* 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
MomentumOpKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
param_out
=
ctx
.
Output
<
Tensor
>
(
"ParamOut"
);
auto
velocity_out
=
ctx
.
Output
<
Tensor
>
(
"VelocityOut"
);
param_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
velocity_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
float
mu
=
ctx
.
Attr
<
float
>
(
"mu"
);
auto
p
=
EigenVector
<
T
>::
Flatten
(
*
ctx
.
Input
<
Tensor
>
(
"Param"
));
auto
g
=
EigenVector
<
T
>::
Flatten
(
*
ctx
.
Input
<
Tensor
>
(
"Grad"
));
auto
v
=
EigenVector
<
T
>::
Flatten
(
*
ctx
.
Input
<
Tensor
>
(
"Velocity"
));
float
lr
=
ctx
.
Input
<
Tensor
>
(
"LearningRate"
)
->
data
<
float
>
()[
0
];
auto
p_out
=
EigenVector
<
T
>::
Flatten
(
*
param_out
);
auto
v_out
=
EigenVector
<
T
>::
Flatten
(
*
velocity_out
);
auto
place
=
ctx
.
GetEigenDevice
<
Place
>
();
v_out
.
device
(
place
)
=
mu
*
v
-
lr
*
g
;
p_out
.
device
(
place
)
=
p
+
v_out
;
}
};
}
// namespace operators
}
// namespace paddle
python/paddle/v2/framework/tests/test_momentum_op.py
0 → 100644
浏览文件 @
d28b3094
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
class
TestMomentumOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"momentum"
param
=
np
.
random
.
random
((
123
,
321
)).
astype
(
"float32"
)
grad
=
np
.
random
.
random
((
123
,
321
)).
astype
(
"float32"
)
velocity
=
np
.
zeros
((
123
,
321
)).
astype
(
"float32"
)
learning_rate
=
np
.
array
([
0.001
]).
astype
(
"float32"
)
mu
=
0.0001
self
.
inputs
=
{
'Param'
:
param
,
'Grad'
:
grad
,
'Velocity'
:
velocity
,
'LearningRate'
:
learning_rate
}
self
.
attrs
=
{
'mu'
:
mu
}
velocity_out
=
mu
*
velocity
-
learning_rate
*
grad
param_out
=
param
+
velocity_out
self
.
outputs
=
{
'ParamOut'
:
param_out
,
'VelocityOut'
:
velocity_out
}
def
test_check_output
(
self
):
self
.
check_output
()
if
__name__
==
"__main__"
:
unittest
.
main
()
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