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体验新版 GitCode,发现更多精彩内容 >>
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aa250718
编写于
11月 17, 2017
作者:
R
ranqiu
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电子邮件补丁
差异文件
add dot_prod_layer
上级
08bc08d6
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
160 addition
and
0 deletion
+160
-0
paddle/gserver/layers/DotProdLayer.cpp
paddle/gserver/layers/DotProdLayer.cpp
+95
-0
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+15
-0
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+9
-0
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+41
-0
未找到文件。
paddle/gserver/layers/DotProdLayer.cpp
0 → 100644
浏览文件 @
aa250718
/* 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 "Layer.h"
#include "paddle/math/Matrix.h"
#include "paddle/utils/Logging.h"
#include "paddle/utils/Stat.h"
namespace
paddle
{
/**
* @brief A layer for computing the dot product of two vectors
* Input1: vector (batchSize * dim)
* Input2: vector (batchSize * dim)
* Output: a matrix: (batchSize * 1)
*/
class
DotProdLayer
:
public
Layer
{
public:
explicit
DotProdLayer
(
const
LayerConfig
&
config
)
:
Layer
(
config
)
{}
~
DotProdLayer
()
{}
bool
init
(
const
LayerMap
&
layerMap
,
const
ParameterMap
&
parameterMap
)
override
;
void
forward
(
PassType
passType
)
override
;
void
backward
(
const
UpdateCallback
&
callback
=
nullptr
)
override
;
};
REGISTER_LAYER
(
dot_prod
,
DotProdLayer
);
bool
DotProdLayer
::
init
(
const
LayerMap
&
layerMap
,
const
ParameterMap
&
parameterMap
)
{
Layer
::
init
(
layerMap
,
parameterMap
);
CHECK_EQ
(
inputLayers_
.
size
(),
2U
);
CHECK_EQ
(
1
,
getSize
())
<<
"Dimension mismatch"
;
return
true
;
}
void
DotProdLayer
::
forward
(
PassType
passType
)
{
Layer
::
forward
(
passType
);
MatrixPtr
inV0
=
getInputValue
(
0
);
MatrixPtr
inV1
=
getInputValue
(
1
);
size_t
batchSize
=
inV0
->
getHeight
();
CHECK_EQ
(
inV1
->
getHeight
(),
batchSize
);
{
REGISTER_TIMER_INFO
(
"FwResetTimer"
,
getName
().
c_str
());
reserveOutput
(
batchSize
,
1
);
}
MatrixPtr
outV
=
getOutputValue
();
{
REGISTER_TIMER_INFO
(
"FwDotProdTimer"
,
getName
().
c_str
());
outV
->
sumOfProducts
(
*
inV0
,
*
inV1
,
1
,
0
);
}
}
void
DotProdLayer
::
backward
(
const
UpdateCallback
&
callback
)
{
MatrixPtr
inV0
=
getInputValue
(
0
);
MatrixPtr
inV1
=
getInputValue
(
1
);
MatrixPtr
outG
=
getOutputGrad
();
MatrixPtr
inG0
=
getInputGrad
(
0
);
MatrixPtr
inG1
=
getInputGrad
(
1
);
{
REGISTER_TIMER_INFO
(
"BwDotProdTimer"
,
getName
().
c_str
());
if
(
inG0
)
{
inG0
->
addRowScale
(
0
,
*
inV1
,
*
outG
);
}
if
(
inG1
)
{
inG1
->
addRowScale
(
0
,
*
inV0
,
*
outG
);
}
}
}
}
// namespace paddle
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
aa250718
...
...
@@ -1081,6 +1081,21 @@ TEST(Layer, InterpolationLayer) {
}
}
TEST
(
Layer
,
DotProdLayer
)
{
TestConfig
config
;
config
.
layerConfig
.
set_type
(
"dot_prod"
);
config
.
layerConfig
.
set_size
(
1
);
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_0"
,
10
,
0
});
config
.
layerConfig
.
add_inputs
();
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"layer_1"
,
10
,
0
});
config
.
layerConfig
.
add_inputs
();
for
(
auto
useGpu
:
{
false
,
true
})
{
testLayerGrad
(
config
,
"dot_prod"
,
100
,
false
,
useGpu
);
}
}
TEST
(
Layer
,
OuterProdLayer
)
{
TestConfig
config
;
config
.
layerConfig
.
set_type
(
"out_prod"
);
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
aa250718
...
...
@@ -3209,6 +3209,15 @@ class SubNestedSequenceLayer(LayerBase):
self
.
set_layer_size
(
size
)
@
config_layer
(
'dot_prod'
)
class
DotProdLayer
(
LayerBase
):
def
__init__
(
self
,
name
,
inputs
,
device
=
None
):
super
(
DotProdLayer
,
self
).
__init__
(
name
,
'dot_prod'
,
0
,
inputs
,
device
=
device
)
config_assert
(
len
(
inputs
)
==
2
,
'DotProdLayer must have 2 inputs'
)
self
.
set_layer_size
(
1
)
@
config_layer
(
'out_prod'
)
class
OuterProdLayer
(
LayerBase
):
def
__init__
(
self
,
name
,
inputs
,
device
=
None
):
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
aa250718
...
...
@@ -115,6 +115,7 @@ __all__ = [
'huber_classification_cost'
,
'block_expand_layer'
,
'maxout_layer'
,
'dot_prod_layer'
,
'out_prod_layer'
,
'printer_layer'
,
'print_layer'
,
...
...
@@ -197,6 +198,7 @@ class LayerType(object):
SCALING_LAYER
=
'scaling'
TRANS_LAYER
=
'trans'
ROTATE_LAYER
=
'rotate'
DOT_PROD_LAYER
=
'dot_prod'
OUT_PROD_LAYER
=
'out_prod'
FEATURE_MAP_EXPAND_LAYER
=
'featmap_expand'
...
...
@@ -4140,6 +4142,45 @@ def maxid_layer(input, name=None, layer_attr=None):
size
=
l
.
config
.
size
)
@
wrap_name_default
()
def
dot_prod_layer
(
input1
,
input2
,
name
=
None
,
layer_attr
=
None
):
"""
A layer for computing the dot product of two vectors.
The example usage is:
.. code-block:: python
dot_prod = dot_prod_layer(input1=vec1, input2=vec2)
:param name: The name of this layer. It is optional.
:type name: basestring
:param input1: The first input layer.
:type input: LayerOutput
:param input2: The second input layer.
:type input2: LayerOutput
:param layer_attr: The extra layer attribute. See ExtraLayerAttribute for
details.
:type layer_attr: ExtraLayerAttribute.
:return: LayerOutput object.
:rtype: LayerOutput
"""
assert
isinstance
(
input1
,
LayerOutput
)
assert
isinstance
(
input2
,
LayerOutput
)
assert
input1
.
size
==
input2
.
size
,
(
"Two inputs should have the same size."
)
l
=
Layer
(
name
=
name
,
type
=
LayerType
.
DOT_PROD_LAYER
,
inputs
=
[
input1
.
name
,
input2
.
name
],
**
ExtraLayerAttribute
.
to_kwargs
(
layer_attr
))
return
LayerOutput
(
name
=
name
,
layer_type
=
LayerType
.
DOT_PROD_LAYER
,
parents
=
[
input1
,
input2
],
size
=
l
.
config
.
size
)
@
wrap_name_default
()
def
out_prod_layer
(
input1
,
input2
,
name
=
None
,
layer_attr
=
None
):
"""
...
...
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