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体验新版 GitCode,发现更多精彩内容 >>
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ceefb555
编写于
10月 10, 2017
作者:
T
Tao Luo
提交者:
GitHub
10月 10, 2017
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差异文件
Merge pull request #4500 from luotao1/interp
add interpolation op
上级
b33779d6
a06f099d
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
141 addition
and
0 deletion
+141
-0
paddle/operators/interp_op.cc
paddle/operators/interp_op.cc
+113
-0
python/paddle/v2/framework/tests/test_interp_op.py
python/paddle/v2/framework/tests/test_interp_op.py
+28
-0
未找到文件。
paddle/operators/interp_op.cc
0 → 100644
浏览文件 @
ceefb555
/* 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/framework/op_registry.h"
#include "paddle/operators/net_op.h"
namespace
paddle
{
namespace
operators
{
class
InterpOp
:
public
NetOp
{
public:
InterpOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
NetOp
(
type
,
inputs
,
outputs
,
attrs
)
{
PADDLE_ENFORCE_NE
(
Input
(
"X"
),
framework
::
kEmptyVarName
,
"Input(X) of InterpOp should not be null."
);
PADDLE_ENFORCE_NE
(
Input
(
"Y"
),
framework
::
kEmptyVarName
,
"Input(Y) of InterpOp should not be null."
);
PADDLE_ENFORCE_NE
(
Input
(
"W"
),
framework
::
kEmptyVarName
,
"Input(W) of InterpOp should not be null."
);
PADDLE_ENFORCE_NE
(
Output
(
"SubOut"
),
framework
::
kEmptyVarName
,
"Output(SubOut) of InterpOp should not be null."
);
PADDLE_ENFORCE_NE
(
Output
(
"MulOut"
),
framework
::
kEmptyVarName
,
"Output(MulOut) of InterpOp should not be null."
);
PADDLE_ENFORCE_NE
(
Output
(
"Out"
),
framework
::
kEmptyVarName
,
"Output(Out) of InterpOp should not be null."
);
// SubOut = X - Y
auto
x
=
Input
(
"X"
);
auto
y
=
Input
(
"Y"
);
auto
sub_out
=
Output
(
"SubOut"
);
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"elementwise_sub"
,
{{
"X"
,
{
x
}},
{
"Y"
,
{
y
}}},
{{
"Out"
,
{
sub_out
}}},
{}));
// MulOut = SubOut * W = (X - Y) * W
auto
w
=
Input
(
"W"
);
auto
mul_out
=
Output
(
"MulOut"
);
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"elementwise_mul"
,
{{
"X"
,
{
sub_out
}},
{
"Y"
,
{
w
}}},
{{
"Out"
,
{
mul_out
}}},
{{
"axis"
,
0
}}));
// Out = MulOut + Y = (X - Y) * W + Y = X * W + Y * (1 - W)
AppendOp
(
framework
::
OpRegistry
::
CreateOp
(
"elementwise_add"
,
{{
"X"
,
{
mul_out
}},
{
"Y"
,
{
y
}}},
{{
"Out"
,
{
Output
(
"Out"
)}}},
{}));
CompleteAddOp
(
false
);
}
};
class
InterpOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
InterpOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"(Tensor), 2-D Matrix of shape [batch_size, data_dim]"
"containing data samples, the first input of interp_op"
);
AddInput
(
"Y"
,
"(Tensor), 2-D Matrix of shape `[batch_size, data_dim]`"
"containing data samples, the second input of interp_op"
);
AddInput
(
"W"
,
"(Tensor), 1-D Vector of shape [batch_size],"
"the interpolated values in the half-open interval [0.0, 1.0)"
);
AddOutput
(
"SubOut"
,
"(Tensor), the intermediate subtraction outputs, saving X - Y."
)
.
AsIntermediate
();
AddOutput
(
"MulOut"
,
"(Tensor), the intermediate multiplication outputs,"
"saving the elementwise multiplication of (X - Y) and W."
)
.
AsIntermediate
();
AddOutput
(
"Out"
,
"(Tensor), the output of interp_op, same shape with X,"
"returns the first-dimensional piecewise linear interpolant "
"between X and Y"
);
AddComment
(
R"DOC(
Linear Interpolation with two inputs, used in NEURAL TURING MACHINE.
Equation:
Out.row[i] = X.row[i] * W[i] + Y.row[i] * (1 - W[i])
= (X.row[i] - Y.row[i]) * W[i] + Y.row[i]
Example:
X = [[1,2],[3,4]],
Y = [[2,1],[4,3]],
W = [0.3, 0.4]
Then, Out = [[1.7,1.3],[3.6,3.4]]
where 1.7 = 1*0.3+2*(1-0.3),
1.3 = 2*0.3+1*(1-0.3),
3.6 = 3*0.4+4*(1-0.4),
3.4 = 4*0.4+3*(1-0.4)
)DOC"
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_WITHOUT_GRADIENT
(
interp
,
ops
::
InterpOp
,
ops
::
InterpOpMaker
);
python/paddle/v2/framework/tests/test_interp_op.py
0 → 100644
浏览文件 @
ceefb555
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
class
TestInterpOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"interp"
x
=
np
.
random
.
random
((
2
,
3
)).
astype
(
"float32"
)
y
=
np
.
random
.
random
((
2
,
3
)).
astype
(
"float32"
)
w
=
np
.
random
.
random
(
2
).
astype
(
"float32"
)
sub_out
=
x
-
y
mul_out
=
sub_out
*
w
.
reshape
(
2
,
1
)
out
=
mul_out
+
y
self
.
inputs
=
{
'X'
:
x
,
'Y'
:
y
,
'W'
:
w
}
self
.
outputs
=
{
'Out'
:
out
,
'SubOut'
:
sub_out
,
'MulOut'
:
mul_out
}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad_normal
(
self
):
self
.
check_grad
([
'X'
,
'Y'
],
'Out'
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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