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23a8d015
编写于
7月 30, 2017
作者:
G
guosheng
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差异文件
add ClipLayer
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0973c2c9
变更
7
隐藏空白更改
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并排
Showing
7 changed file
with
190 addition
and
97 deletion
+190
-97
paddle/gserver/layers/ClipLayer.cpp
paddle/gserver/layers/ClipLayer.cpp
+78
-0
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+15
-0
paddle/math/BaseMatrix.cu
paddle/math/BaseMatrix.cu
+6
-0
paddle/math/BaseMatrix.h
paddle/math/BaseMatrix.h
+7
-0
proto/ModelConfig.proto
proto/ModelConfig.proto
+6
-0
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+17
-0
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+61
-97
未找到文件。
paddle/gserver/layers/ClipLayer.cpp
0 → 100644
浏览文件 @
23a8d015
/* 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"
namespace
paddle
{
/**
* A layer for clipping the input value by the threshold.
* \f[
* out[i] = \min\left(\max\left(in[i],p_{1}\right),p_{2}\right)
* \f]
*/
class
ClipLayer
:
public
Layer
{
protected:
real
clipThresholdLow_
;
real
clipThresholdHigh_
;
public:
explicit
ClipLayer
(
const
LayerConfig
&
config
)
:
Layer
(
config
)
{}
bool
init
(
const
LayerMap
&
layerMap
,
const
ParameterMap
&
parameterMap
)
override
;
void
forward
(
PassType
passType
)
override
;
void
backward
(
const
UpdateCallback
&
callback
=
nullptr
)
override
;
};
REGISTER_LAYER
(
clip
,
ClipLayer
);
bool
ClipLayer
::
init
(
const
LayerMap
&
layerMap
,
const
ParameterMap
&
parameterMap
)
{
Layer
::
init
(
layerMap
,
parameterMap
);
CHECK_EQ
(
inputLayers_
.
size
(),
1U
);
auto
layerConf
=
config_
.
inputs
(
0
).
clip_conf
();
clipThresholdLow_
=
layerConf
.
clip_threshold_low
();
clipThresholdHigh_
=
layerConf
.
clip_threshold_high
();
CHECK_LT
(
clipThresholdLow_
,
clipThresholdHigh_
);
return
true
;
}
void
ClipLayer
::
forward
(
PassType
passType
)
{
Layer
::
forward
(
passType
);
MatrixPtr
inV
=
getInputValue
(
0
);
resetOutput
(
inV
->
getHeight
(),
inV
->
getWidth
());
MatrixPtr
outV
=
getOutputValue
();
outV
->
copyFrom
(
*
inV
);
outV
->
clip
(
clipThresholdLow_
,
clipThresholdHigh_
);
}
void
ClipLayer
::
backward
(
const
UpdateCallback
&
callback
)
{
MatrixPtr
inV
=
getInputValue
(
0
);
MatrixPtr
inG
=
getInputGrad
(
0
);
MatrixPtr
outV
=
getOutputValue
();
MatrixPtr
outG
=
getOutputGrad
();
MatrixPtr
tmpMtx
;
Matrix
::
resizeOrCreate
(
tmpMtx
,
outG
->
getHeight
(),
outG
->
getWidth
(),
false
,
useGpu_
);
tmpMtx
->
clipDerivative
(
*
inV
,
clipThresholdLow_
,
clipThresholdHigh_
);
inG
->
addDotMul
(
*
outG
,
*
tmpMtx
,
1
,
1
);
}
}
// namespace paddle
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
23a8d015
...
...
@@ -1879,6 +1879,21 @@ TEST(Layer, CropLayer) {
}
}
TEST
(
Layer
,
ClipLayer
)
{
const
size_t
batchSize
=
128
;
const
size_t
size
=
512
;
TestConfig
config
;
config
.
layerConfig
.
set_type
(
"clip"
);
config
.
inputDefs
.
push_back
({
INPUT_DATA
,
"input"
,
size
,
0
});
LayerInputConfig
*
input
=
config
.
layerConfig
.
add_inputs
();
ClipConfig
*
layerConf
=
input
->
mutable_clip_conf
();
layerConf
->
set_clip_threshold_low
(
std
::
rand
()
/
(
real
)
RAND_MAX
);
layerConf
->
set_clip_threshold_high
(
std
::
rand
()
/
(
real
)
RAND_MAX
);
for
(
auto
useGpu
:
{
false
,
true
})
{
testLayerGrad
(
config
,
"clip"
,
batchSize
,
false
,
useGpu
,
false
);
}
}
int
main
(
int
argc
,
char
**
argv
)
{
testing
::
InitGoogleTest
(
&
argc
,
argv
);
initMain
(
argc
,
argv
);
...
...
paddle/math/BaseMatrix.cu
浏览文件 @
23a8d015
...
...
@@ -442,6 +442,12 @@ DEFINE_MATRIX_UNARY_PARAMETER_OP(Clip, TWO_PARAMETER,
template
<
class
T
>
void
BaseMatrixT
<
T
>::
clip
(
T
p1
,
T
p2
)
{
applyUnary
(
unary
::
Clip
<
T
>
(
p1
,
p2
));
}
DEFINE_MATRIX_BINARY_PARAMETER_OP
(
ClipDerivative
,
TWO_PARAMETER
,
a
=
b
<
p1
?
0
:
(
b
>
p2
?
0
:
1
));
template
<
class
T
>
void
BaseMatrixT
<
T
>::
clipDerivative
(
BaseMatrixT
&
b
,
T
p1
,
T
p2
)
{
applyBinary
(
binary
::
ClipDerivative
<
T
>
(
p1
,
p2
),
b
);
}
DEFINE_MATRIX_UNARY_PARAMETER_OP
(
BiggerThanScalar
,
ONE_PARAMETER
,
a
=
a
>
p
?
1.0
f
:
0.0
f
);
template
<
class
T
>
...
...
paddle/math/BaseMatrix.h
浏览文件 @
23a8d015
...
...
@@ -488,6 +488,13 @@ public:
*/
void
clip
(
T
p1
,
T
p2
);
/**
* this = b < low ? 0 : 1
*
* this = b > high ? 0 : 1
*/
void
clipDerivative
(
BaseMatrixT
&
b
,
T
p1
,
T
p2
);
/**
* @code
* a = a > p ? 1.0f : 0.0f
...
...
proto/ModelConfig.proto
浏览文件 @
23a8d015
...
...
@@ -289,6 +289,11 @@ message DetectionOutputConfig {
optional
uint32
width
=
9
[
default
=
1
];
}
message
ClipConfig
{
required
float
clip_threshold_low
=
1
;
required
float
clip_threshold_high
=
2
;
}
message
LayerInputConfig
{
required
string
input_layer_name
=
1
;
optional
string
input_parameter_name
=
2
;
...
...
@@ -309,6 +314,7 @@ message LayerInputConfig {
optional
RowConvConfig
row_conv_conf
=
15
;
optional
MultiBoxLossConfig
multibox_loss_conf
=
16
;
optional
DetectionOutputConfig
detection_output_conf
=
17
;
optional
ClipConfig
clip_conf
=
18
;
}
message
LayerConfig
{
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
23a8d015
...
...
@@ -2169,6 +2169,23 @@ class RowConvLayer(LayerBase):
self
.
create_input_parameter
(
0
,
psize
,
dims
)
@
config_layer
(
'clip'
)
class
ClipLayer
(
LayerBase
):
def
__init__
(
self
,
name
,
inputs
,
clip_threshold_low
,
clip_threshold_high
):
super
(
ClipLayer
,
self
).
__init__
(
name
,
'clip'
,
0
,
inputs
=
inputs
)
config_assert
(
len
(
self
.
inputs
)
==
1
,
'ClipLayer layer must have one and only one input.'
)
config_assert
(
clip_threshold_low
<
clip_threshold_high
,
'clip_threshold_low must be less than clip_threshold_high.'
)
input_layer
=
self
.
get_input_layer
(
0
)
self
.
set_layer_size
(
input_layer
.
size
)
self
.
config
.
inputs
[
0
].
clip_conf
.
clip_threshold_low
=
clip_threshold_low
self
.
config
.
inputs
[
0
].
clip_conf
.
clip_threshold_high
=
clip_threshold_high
# key: cost type
# value: cost class
g_cost_map
=
{}
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
23a8d015
...
...
@@ -31,103 +31,33 @@ except ImportError:
import
copy
__all__
=
[
'full_matrix_projection'
,
'AggregateLevel'
,
'ExpandLevel'
,
'identity_projection'
,
'dotmul_projection'
,
'dotmul_operator'
,
'repeat_layer'
,
'seq_reshape_layer'
,
'table_projection'
,
'mixed_layer'
,
'data_layer'
,
'embedding_layer'
,
'fc_layer'
,
'grumemory'
,
'pooling_layer'
,
'lstmemory'
,
'last_seq'
,
'first_seq'
,
'cos_sim'
,
'hsigmoid'
,
'conv_projection'
,
'mse_cost'
,
'regression_cost'
,
'classification_cost'
,
'LayerOutput'
,
'img_conv_layer'
,
'img_pool_layer'
,
'batch_norm_layer'
,
'img_cmrnorm_layer'
,
'addto_layer'
,
'concat_layer'
,
'seq_concat_layer'
,
'lstm_step_layer'
,
'recurrent_group'
,
'memory'
,
'StaticInput'
,
'expand_layer'
,
'scaling_layer'
,
'scaling_projection'
,
'power_layer'
,
'interpolation_layer'
,
'bilinear_interp_layer'
,
'trans_layer'
,
'rotate_layer'
,
'sum_to_one_norm_layer'
,
'get_output_layer'
,
'LayerType'
,
'context_projection'
,
'beam_search'
,
'maxid_layer'
,
'GeneratedInput'
,
'SubsequenceInput'
,
'gru_step_layer'
,
'gru_step_naive_layer'
,
'recurrent_layer'
,
'BaseGeneratedInput'
,
'conv_operator'
,
'conv_shift_layer'
,
'tensor_layer'
,
'selective_fc_layer'
,
'sampling_id_layer'
,
'slope_intercept_layer'
,
'trans_full_matrix_projection'
,
'linear_comb_layer'
,
'convex_comb_layer'
,
'ctc_layer'
,
'warp_ctc_layer'
,
'crf_layer'
,
'crf_decoding_layer'
,
'nce_layer'
,
'cross_entropy_with_selfnorm'
,
'cross_entropy'
,
'multi_binary_label_cross_entropy'
,
'sum_cost'
,
'rank_cost'
,
'lambda_cost'
,
'huber_cost'
,
'block_expand_layer'
,
'maxout_layer'
,
'out_prod_layer'
,
'printer_layer'
,
'print_layer'
,
'priorbox_layer'
,
'cross_channel_norm_layer'
,
'multibox_loss_layer'
,
'detection_output_layer'
,
'spp_layer'
,
'pad_layer'
,
'eos_layer'
,
'smooth_l1_cost'
,
'layer_support'
,
'multiplex_layer'
,
'row_conv_layer'
,
'dropout_layer'
,
'prelu_layer'
,
'gated_unit_layer'
,
'crop_layer'
,
'full_matrix_projection'
,
'AggregateLevel'
,
'ExpandLevel'
,
'identity_projection'
,
'dotmul_projection'
,
'dotmul_operator'
,
'repeat_layer'
,
'seq_reshape_layer'
,
'table_projection'
,
'mixed_layer'
,
'data_layer'
,
'embedding_layer'
,
'fc_layer'
,
'grumemory'
,
'pooling_layer'
,
'lstmemory'
,
'last_seq'
,
'first_seq'
,
'cos_sim'
,
'hsigmoid'
,
'conv_projection'
,
'mse_cost'
,
'regression_cost'
,
'classification_cost'
,
'LayerOutput'
,
'img_conv_layer'
,
'img_pool_layer'
,
'batch_norm_layer'
,
'img_cmrnorm_layer'
,
'addto_layer'
,
'concat_layer'
,
'seq_concat_layer'
,
'lstm_step_layer'
,
'recurrent_group'
,
'memory'
,
'StaticInput'
,
'expand_layer'
,
'scaling_layer'
,
'scaling_projection'
,
'power_layer'
,
'interpolation_layer'
,
'bilinear_interp_layer'
,
'trans_layer'
,
'rotate_layer'
,
'sum_to_one_norm_layer'
,
'get_output_layer'
,
'LayerType'
,
'context_projection'
,
'beam_search'
,
'maxid_layer'
,
'GeneratedInput'
,
'SubsequenceInput'
,
'gru_step_layer'
,
'gru_step_naive_layer'
,
'recurrent_layer'
,
'BaseGeneratedInput'
,
'conv_operator'
,
'conv_shift_layer'
,
'tensor_layer'
,
'selective_fc_layer'
,
'sampling_id_layer'
,
'slope_intercept_layer'
,
'trans_full_matrix_projection'
,
'linear_comb_layer'
,
'convex_comb_layer'
,
'ctc_layer'
,
'warp_ctc_layer'
,
'crf_layer'
,
'crf_decoding_layer'
,
'nce_layer'
,
'cross_entropy_with_selfnorm'
,
'cross_entropy'
,
'multi_binary_label_cross_entropy'
,
'sum_cost'
,
'rank_cost'
,
'lambda_cost'
,
'huber_cost'
,
'block_expand_layer'
,
'maxout_layer'
,
'out_prod_layer'
,
'printer_layer'
,
'print_layer'
,
'priorbox_layer'
,
'cross_channel_norm_layer'
,
'multibox_loss_layer'
,
'detection_output_layer'
,
'spp_layer'
,
'pad_layer'
,
'eos_layer'
,
'smooth_l1_cost'
,
'layer_support'
,
'multiplex_layer'
,
'row_conv_layer'
,
'dropout_layer'
,
'prelu_layer'
,
'gated_unit_layer'
,
'crop_layer'
,
'clip_layer'
]
...
...
@@ -220,6 +150,7 @@ class LayerType(object):
PRELU
=
'prelu'
CROP_LAYER
=
'crop'
CLIP_LAYER
=
'clip'
@
staticmethod
def
is_layer_type
(
type_name
):
...
...
@@ -6006,3 +5937,36 @@ def crop_layer(input, offset, axis=2, shape=None, name=None, layer_attr=None):
layer_type
=
LayerType
.
CROP_LAYER
,
parents
=
input
,
size
=
l
.
config
.
size
)
@
wrap_name_default
(
"clip"
)
def
clip_layer
(
input
,
clip_threshold_low
,
clip_threshold_high
,
name
=
None
):
"""
A layer for clipping the input value by the threshold.
.. math::
out[i] = \min\left(\max\left(in[i],p_{1}
\r
ight),p_{2}
\r
ight)
.. code-block:: python
clip = clip_layer(input=input_layer, clip_threshold_low=-10, clip_threshold_high=10)
:param name: The Layer Name.
:type name: basestring
:param input: The input layer.
:type input: LayerOutput.
:param clip_threshold_low: The lower threshold for clipping.
:type clip_threshold_low: float
:param clip_threshold_high: The upper threshold for clipping.
:type clip_threshold_high: float
:return: LayerOutput
"""
Layer
(
name
=
name
,
type
=
LayerType
.
CLIP_LAYER
,
inputs
=
[
input
.
name
],
clip_threshold_low
=
clip_threshold_low
,
clip_threshold_high
=
clip_threshold_high
)
return
LayerOutput
(
name
,
LayerType
.
CLIP_LAYER
,
parents
=
[
input
],
size
=
input
.
size
)
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