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aaf8401f
编写于
8月 01, 2017
作者:
H
hedaoyuan
提交者:
GitHub
8月 01, 2017
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差异文件
Merge pull request #3126 from hedaoyuan/slice
Slice Layer
上级
4f1061f7
90846f3c
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
286 addition
and
0 deletion
+286
-0
doc/api/v2/config/layer.rst
doc/api/v2/config/layer.rst
+4
-0
paddle/gserver/layers/SliceProjection.cpp
paddle/gserver/layers/SliceProjection.cpp
+96
-0
paddle/gserver/tests/concat_slice_a.conf
paddle/gserver/tests/concat_slice_a.conf
+41
-0
paddle/gserver/tests/concat_slice_b.conf
paddle/gserver/tests/concat_slice_b.conf
+41
-0
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+20
-0
paddle/gserver/tests/test_NetworkCompare.cpp
paddle/gserver/tests/test_NetworkCompare.cpp
+6
-0
proto/ModelConfig.proto
proto/ModelConfig.proto
+9
-0
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+29
-0
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+40
-0
未找到文件。
doc/api/v2/config/layer.rst
浏览文件 @
aaf8401f
...
...
@@ -198,6 +198,10 @@ identity_projection
.. autoclass:: paddle.v2.layer.identity_projection
:noindex:
slice_projection
-------------------
.. autoclass:: paddle.v2.layer.slice_projection
:noindex:
table_projection
----------------
...
...
paddle/gserver/layers/SliceProjection.cpp
0 → 100644
浏览文件 @
aaf8401f
/* 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 "Projection.h"
namespace
paddle
{
/**
* SliceProjection can slice the input value into multiple parts,
* and then select some of them to merge into a new output.
*
* First, calculate the slices that need to be merged into the output.
* slices = input.slices().for_output()
*
* Second, merge each slice into the output.
* for(auto slice: slices) {
* out.addAtOffset(slice, offset);
* }
*
* Input slices as output: s0, s1, ...:
* -----------------------
* |///| |//////| |
* |/s0| |//s1//| |
* |///| |//////| |
* -----------------------
* Output, merge s0, s1, ... into one output:
* ----------------
* |///|//////| |
* |/s0|//s1//|...|
* |///|//////| |
* ----------------
*
* The config file api is slice_projection.
*/
class
SliceProjection
:
public
Projection
{
public:
SliceProjection
(
const
ProjectionConfig
&
config
,
const
ParameterPtr
&
parameter
,
bool
useGpu
);
virtual
void
forward
();
virtual
void
backward
(
const
UpdateCallback
&
callback
);
protected:
std
::
vector
<
std
::
pair
<
size_t
,
size_t
>>
slices_
;
};
REGISTER_PROJECTION
(
slice
,
SliceProjection
);
/**
* Constructed function.
* @note SliceProjection should not have any parameter.
*/
SliceProjection
::
SliceProjection
(
const
ProjectionConfig
&
config
,
const
ParameterPtr
&
parameter
,
bool
useGpu
)
:
Projection
(
config
,
parameter
,
useGpu
)
{
CHECK
(
!
parameter
)
<<
"'slice' projection should not have any parameter"
;
slices_
.
reserve
(
config
.
slices_size
());
for
(
const
auto
&
slice
:
config
.
slices
())
{
slices_
.
push_back
(
std
::
make_pair
(
slice
.
start
(),
slice
.
end
()));
}
}
void
SliceProjection
::
forward
()
{
size_t
offset
=
0
;
for
(
auto
&
slice
:
slices_
)
{
auto
slice_out
=
in_
->
value
->
subColMatrix
(
slice
.
first
,
slice
.
second
);
out_
->
value
->
addAtOffset
(
*
slice_out
,
offset
);
offset
+=
slice_out
->
getWidth
();
}
}
void
SliceProjection
::
backward
(
const
UpdateCallback
&
callback
)
{
if
(
in_
->
grad
)
{
size_t
offset
=
0
;
for
(
auto
&
slice
:
slices_
)
{
auto
slice_out
=
in_
->
grad
->
subColMatrix
(
slice
.
first
,
slice
.
second
);
slice_out
->
addAtOffset
(
*
out_
->
grad
,
offset
);
offset
+=
slice_out
->
getWidth
();
}
}
}
}
// namespace paddle
paddle/gserver/tests/concat_slice_a.conf
0 → 100644
浏览文件 @
aaf8401f
#edit-mode: -*- python -*-
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
# 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.
from
paddle
.
trainer_config_helpers
import
*
settings
(
batch_size
=
10
)
data
=
data_layer
(
name
=
"input"
,
size
=
8
*
16
*
16
)
conv1
=
img_conv_layer
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
False
,
act
=
ReluActivation
())
conv2
=
img_conv_layer
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
False
,
act
=
ReluActivation
())
proj1
=
slice_projection
(
input
=
conv1
,
slices
=[(
0
,
4
), (
4
,
12
)])
proj2
=
slice_projection
(
input
=
conv2
,
slices
=[(
1
,
5
), (
5
,
15
)])
concat
=
concat_layer
(
input
=[
proj1
,
proj2
])
outputs
(
concat
)
paddle/gserver/tests/concat_slice_b.conf
0 → 100644
浏览文件 @
aaf8401f
#edit-mode: -*- python -*-
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
# 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.
from
paddle
.
trainer_config_helpers
import
*
settings
(
batch_size
=
10
)
data
=
data_layer
(
name
=
"input"
,
size
=
8
*
16
*
16
)
conv1
=
img_conv_layer
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
False
,
act
=
ReluActivation
())
conv2
=
img_conv_layer
(
input
=
data
,
filter_size
=
1
,
filter_size_y
=
1
,
num_channels
=
8
,
num_filters
=
16
,
stride
=
1
,
bias_attr
=
False
,
act
=
ReluActivation
())
proj1
=
slice_projection
(
input
=
conv1
,
slices
=[(
0
,
12
)])
proj2
=
slice_projection
(
input
=
conv2
,
slices
=[(
1
,
15
)])
concat
=
concat_layer
(
input
=[
proj1
,
proj2
])
outputs
(
concat
)
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
aaf8401f
...
...
@@ -152,6 +152,26 @@ TEST(Projection, identity) {
}
}
TEST
(
Projection
,
slice
)
{
ProjectionConfig
conf
;
conf
.
set_type
(
"slice"
);
conf
.
set_input_size
(
100
);
SliceConfig
&
slice1
=
*
conf
.
add_slices
();
slice1
.
set_start
(
10
);
slice1
.
set_end
(
20
);
SliceConfig
&
slice2
=
*
conf
.
add_slices
();
slice2
.
set_start
(
50
);
slice2
.
set_end
(
70
);
conf
.
set_output_size
(
30
);
for
(
auto
useGpu
:
{
false
,
true
})
{
testProjectionGrad
(
conf
,
INPUT_DATA
,
/* parameterSize */
0
,
/* batchSize */
10
,
useGpu
);
}
}
TEST
(
Projection
,
scaling
)
{
ProjectionConfig
conf
;
conf
.
set_type
(
"scaling"
);
...
...
paddle/gserver/tests/test_NetworkCompare.cpp
浏览文件 @
aaf8401f
...
...
@@ -237,6 +237,12 @@ TEST(Compare, concat_table) {
compareNetwork
(
config_file_a
,
config_file_b
);
}
TEST
(
Compare
,
concat_slice
)
{
std
::
string
config_file_a
=
"./gserver/tests/concat_slice_a.conf"
;
std
::
string
config_file_b
=
"./gserver/tests/concat_slice_b.conf"
;
compareNetwork
(
config_file_a
,
config_file_b
);
}
#ifndef PADDLE_ONLY_CPU
TEST
(
Compare
,
img_pool
)
{
std
::
string
config_file_a
=
"./gserver/tests/img_pool_a.conf"
;
...
...
proto/ModelConfig.proto
浏览文件 @
aaf8401f
...
...
@@ -198,6 +198,11 @@ message RowConvConfig {
required
uint32
context_length
=
1
;
}
message
SliceConfig
{
required
uint32
start
=
1
;
required
uint32
end
=
2
;
}
message
ProjectionConfig
{
required
string
type
=
1
;
required
string
name
=
2
;
...
...
@@ -218,6 +223,10 @@ message ProjectionConfig {
// For pool
optional
PoolConfig
pool_conf
=
12
;
// For slice
// Each slice output is the input[start, end)
repeated
SliceConfig
slices
=
13
;
}
message
OperatorConfig
{
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
aaf8401f
...
...
@@ -565,6 +565,35 @@ class IdentityOffsetProjection(Projection):
return
[]
@
config_class
class
SliceProjection
(
Projection
):
type
=
'slice'
def
__init__
(
self
,
input_layer_name
,
slices
,
**
xargs
):
super
(
SliceProjection
,
self
).
__init__
(
input_layer_name
,
**
xargs
)
input
=
g_layer_map
[
input_layer_name
]
if
input
.
type
in
[
"exconv"
,
"cudnn_conv"
]:
# the slice operator is for the channel dimension
assert
input
.
num_filters
is
not
None
channels
=
input
.
num_filters
image_size
=
input
.
size
/
channels
assert
slices
[
len
(
slices
)
-
1
][
1
]
<=
channels
for
i
in
xrange
(
len
(
slices
)):
slice
=
self
.
proj_conf
.
slices
.
add
()
slice
.
start
=
slices
[
i
][
0
]
*
image_size
slice
.
end
=
slices
[
i
][
1
]
*
image_size
self
.
size
+=
slice
.
end
-
slice
.
start
else
:
config_assert
(
False
,
'Currently the input should be convolution layer'
)
def
calc_parameter_size
(
self
,
input_size
,
output_size
):
return
0
def
calc_parameter_dims
(
self
,
input_size
,
output_size
):
return
[]
# DotMulProjection performs element-wise multiplication with weight
@
config_class
class
DotMulProjection
(
Projection
):
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
aaf8401f
...
...
@@ -128,6 +128,7 @@ __all__ = [
'prelu_layer'
,
'gated_unit_layer'
,
'crop_layer'
,
'slice_projection'
,
]
...
...
@@ -536,6 +537,45 @@ def identity_projection(input, offset=None, size=None):
return
proj
def
slice_projection
(
input
,
slices
):
"""
slice_projection can slice the input value into multiple parts,
and then select some of them to merge into a new output.
.. math::
output = [input.slices()]
The example usage is:
.. code-block:: python
proj = slice_projection(input=layer, slices=[(0, 10), (20, 30)])
Note that slice_projection should not have any parameter.
:param input: Input Layer.
:type input: LayerOutput
:param slices: An array of slice parameters.
Each slice contains the start and end offsets based
on the input.
:type slices: pair of int
:return: A SliceProjection object
:rtype: SliceProjection
"""
assert
len
(
slices
)
>=
1
start
=
0
for
i
in
xrange
(
len
(
slices
)):
assert
len
(
slices
[
i
])
==
2
# The start position of the next slice needs to be greater than
# or equal to the end position of the previous slice.
assert
slices
[
i
][
0
]
>=
start
assert
slices
[
i
][
1
]
>=
slices
[
i
][
0
]
start
=
slices
[
i
][
1
]
proj
=
SliceProjection
(
input_layer_name
=
input
.
name
,
slices
=
slices
)
proj
.
origin
=
input
return
proj
@
wrap_param_attr_default
()
def
scaling_projection
(
input
,
param_attr
=
None
):
"""
...
...
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