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体验新版 GitCode,发现更多精彩内容 >>
提交
7f380c1b
编写于
7月 05, 2017
作者:
T
Tao Luo
提交者:
GitHub
7月 05, 2017
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差异文件
Merge pull request #2701 from luotao1/stride
stride pooling for max and average layer
上级
98378968
e7b071f3
变更
13
隐藏空白更改
内联
并排
Showing
13 changed file
with
117 addition
and
23 deletion
+117
-23
paddle/gserver/layers/AverageLayer.h
paddle/gserver/layers/AverageLayer.h
+4
-0
paddle/gserver/layers/MaxLayer.h
paddle/gserver/layers/MaxLayer.h
+4
-0
paddle/gserver/layers/SequenceLastInstanceLayer.cpp
paddle/gserver/layers/SequenceLastInstanceLayer.cpp
+4
-6
paddle/gserver/layers/SequencePoolLayer.cpp
paddle/gserver/layers/SequencePoolLayer.cpp
+2
-3
paddle/gserver/layers/SequencePoolLayer.h
paddle/gserver/layers/SequencePoolLayer.h
+3
-4
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+10
-2
paddle/parameter/Argument.cpp
paddle/parameter/Argument.cpp
+3
-3
paddle/parameter/Argument.h
paddle/parameter/Argument.h
+1
-1
paddle/parameter/tests/test_argument.cpp
paddle/parameter/tests/test_argument.cpp
+2
-2
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+8
-0
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+17
-2
python/paddle/trainer_config_helpers/tests/configs/protostr/test_sequence_pooling.protostr
...ers/tests/configs/protostr/test_sequence_pooling.protostr
+51
-0
python/paddle/trainer_config_helpers/tests/configs/test_sequence_pooling.py
...ner_config_helpers/tests/configs/test_sequence_pooling.py
+8
-0
未找到文件。
paddle/gserver/layers/AverageLayer.h
浏览文件 @
7f380c1b
...
...
@@ -25,6 +25,10 @@ namespace paddle {
* If SequenceLevel = kNonSeq:
* Output: output size is the number of input sequences (NOT input instances)
* output[i] = average_{for each instance in this sequence}{input[i]}
* If stride_ > 0:
* Output: a shorten sequence. Stride is the step size by which we slide a
* window upon the input sequence, and the average pooling
* operation is then applied to each interval independently.
* If SequenceLevel = kSeq:
* Check input sequence must has sub-sequence
* Output: output size is the number of input sub-sequences
...
...
paddle/gserver/layers/MaxLayer.h
浏览文件 @
7f380c1b
...
...
@@ -26,6 +26,10 @@ namespace paddle {
* If SequenceLevel = kNonSeq:
* Output: output size is the number of input sequences (NOT input instances)
* output[i] = max_{for each instance in this sequence}{input[i]}
* If stride_ > 0:
* Output: a shorten sequence. Stride is the step size by which we slide a
* window upon the input sequence, and the max pooling operation is
* then applied to each interval independently.
* If SequenceLevel = kSeq:
* Check input sequence must has sub-sequence
* Output: output size is the number of input sub-sequences
...
...
paddle/gserver/layers/SequenceLastInstanceLayer.cpp
浏览文件 @
7f380c1b
...
...
@@ -26,10 +26,9 @@ namespace paddle {
* If SequenceLevel = kNonseq:
* Output: a sequence containing only the last instance of the input sequence
* If stride_ > 0:
* Output: a shorten sequence. The operation of getting last instance of a
* sequence is independently performed on every slice of the input
* sequence, which is obtained by sliding a window with the window
* size set to stride_.
* Output: a shorten sequence. Stride is the step size by which we slide a
* window upon the input sequence, and getting last instance
* operation is then applied to each interval independently.
* If SequenceLevel = kSeq:
* Check input sequence must has sub-sequence
* Output: a sequence containing only the last instance of each sub-sequence
...
...
@@ -73,8 +72,7 @@ bool SequenceLastInstanceLayer::init(const LayerMap& layerMap,
void
SequenceLastInstanceLayer
::
forward
(
PassType
passType
)
{
SequencePoolLayer
::
forward
(
passType
);
auto
starts
=
(
stride_
>
0
)
?
stridePositions_
->
getData
()
:
startPositions_
->
getData
(
false
);
auto
starts
=
startPositions_
->
getData
(
false
);
MatrixPtr
inputValue
=
getInputValue
(
0
);
MatrixPtr
outputValue
=
getOutputValue
();
...
...
paddle/gserver/layers/SequencePoolLayer.cpp
浏览文件 @
7f380c1b
...
...
@@ -72,9 +72,8 @@ void SequencePoolLayer::forward(PassType passType) {
if
(
stride_
>
0
)
{
CHECK_EQ
(
input
.
hasSubseq
(),
0UL
)
<<
"sequence stride pooling is invalid for hasSubseq now"
;
output_
.
poolSequenceWithStride
(
input
,
stride_
,
&
stridePositions_
,
reversed_
);
newBatchSize_
=
stridePositions_
->
getSize
()
-
1
;
output_
.
poolSequenceWithStride
(
input
,
stride_
,
&
startPositions_
,
reversed_
);
newBatchSize_
=
startPositions_
->
getSize
()
-
1
;
}
resetOutput
(
newBatchSize_
,
dim
);
...
...
paddle/gserver/layers/SequencePoolLayer.h
浏览文件 @
7f380c1b
...
...
@@ -28,8 +28,9 @@ namespace paddle {
* sequence}{input[i]}
* If stride_ > 0:
* Check input sequence must not have sub-sequence
* Output: a shorten sequence, pooling is performed upon a small local
* area
* Output: a shorten sequence. Stride is the step size by which we slide
* a window upon the input sequence, and the pooling operation
* is then applied to each interval independently.
* If SequenceLevel = kSeq:
* Check input sequence must has sub-sequence
* Output: output size is the number of input sub-sequences
...
...
@@ -47,8 +48,6 @@ protected:
size_t
newBatchSize_
;
ICpuGpuVectorPtr
startPositions_
;
int
stride_
;
// Store the start position of each window.
IVectorPtr
stridePositions_
;
// Whether the input sequence is reversed or not.
bool
reversed_
=
false
;
...
...
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
7f380c1b
...
...
@@ -845,8 +845,12 @@ void testDegradeLayer(bool hasSubseq,
TEST
(
Layer
,
MaxLayer
)
{
testDegradeLayer
(
false
,
"max"
,
"non-seq"
,
-
1
);
// seq max to non-seq
testDegradeLayer
(
true
,
"max"
,
"non-seq"
,
-
1
);
// hasSubseq max to non-seq
testDegradeLayer
(
true
,
"max"
,
"seq"
,
-
1
);
// hasSubseq max to seq
testDegradeLayer
(
false
,
"max"
,
"non-seq"
,
5
);
// seq max to a shorten seq, stride window = 5
testDegradeLayer
(
true
,
"max"
,
"non-seq"
,
-
1
);
// hasSubseq max to non-seq
testDegradeLayer
(
true
,
"max"
,
"seq"
,
-
1
);
// hasSubseq max to seq
}
TEST
(
Layer
,
SequenceLastInstanceLayer
)
{
...
...
@@ -868,6 +872,10 @@ TEST(Layer, SequenceLastInstanceLayer) {
TEST
(
Layer
,
AverageLayer
)
{
testDegradeLayer
(
false
,
"average"
,
"non-seq"
,
-
1
);
// seq average to non-seq
testDegradeLayer
(
false
,
"average"
,
"non-seq"
,
5
);
// seq average to a shorten seq, stride window = 5
testDegradeLayer
(
true
,
"average"
,
"non-seq"
,
-
1
);
// hasSubseq average to non-seq
testDegradeLayer
(
true
,
"average"
,
"seq"
,
-
1
);
// hasSubseq average to seq
...
...
paddle/parameter/Argument.cpp
浏览文件 @
7f380c1b
...
...
@@ -561,7 +561,7 @@ void Argument::degradeSequence(const Argument& input) {
void
Argument
::
poolSequenceWithStride
(
const
Argument
&
input
,
size_t
stride
,
IVectorPtr
*
stridePostions
,
I
CpuGpu
VectorPtr
*
stridePostions
,
bool
reversed
)
{
// If input.sequenceStartPositions = [0, 9, 14, 17, 30] and stride = 5,
// then sequenceStartPositions = [0, 2, 3, 4, 7].
...
...
@@ -598,8 +598,8 @@ void Argument::poolSequenceWithStride(const Argument& input,
stridePos
.
emplace_back
(
starts
[
numSequences
]);
int
size
=
stridePos
.
size
();
CHECK_EQ
(
size
-
1
,
tgtBuf
[
numSequences
]);
IVector
::
resizeOrCreate
(
*
stridePostions
,
size
,
false
);
(
*
stridePostions
)
->
copyFrom
(
stridePos
.
data
(),
size
);
I
CpuGpu
Vector
::
resizeOrCreate
(
*
stridePostions
,
size
,
false
);
(
*
stridePostions
)
->
getMutableVector
(
false
)
->
copyFrom
(
stridePos
.
data
(),
size
);
}
void
Argument
::
getValueString
(
...
...
paddle/parameter/Argument.h
浏览文件 @
7f380c1b
...
...
@@ -299,7 +299,7 @@ struct Argument {
*/
void
poolSequenceWithStride
(
const
Argument
&
input
,
size_t
stride
,
IVectorPtr
*
stridePositions
,
I
CpuGpu
VectorPtr
*
stridePositions
,
bool
reversed
=
false
);
/**
* @brief getValueString will return the argument's output in string. There
...
...
paddle/parameter/tests/test_argument.cpp
浏览文件 @
7f380c1b
...
...
@@ -31,7 +31,7 @@ TEST(Argument, poolSequenceWithStride) {
int
strideResultReversed
[]
=
{
0
,
4
,
9
,
14
,
17
,
20
,
25
,
30
};
for
(
auto
reversed
:
{
false
,
true
})
{
IVectorPtr
stridePositions
;
I
CpuGpu
VectorPtr
stridePositions
;
output
.
poolSequenceWithStride
(
input
,
5
/* stride */
,
&
stridePositions
,
reversed
);
...
...
@@ -45,7 +45,7 @@ TEST(Argument, poolSequenceWithStride) {
CHECK_EQ
(
stridePositions
->
getSize
(),
8UL
);
auto
result
=
reversed
?
strideResultReversed
:
strideResult
;
for
(
int
i
=
0
;
i
<
8
;
i
++
)
{
CHECK_EQ
(
stridePositions
->
getData
()[
i
],
result
[
i
]);
CHECK_EQ
(
stridePositions
->
getData
(
false
)[
i
],
result
[
i
]);
}
}
}
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
7f380c1b
...
...
@@ -2466,10 +2466,14 @@ class MaxLayer(LayerBase):
trans_type
=
'non-seq'
,
bias
=
False
,
output_max_index
=
None
,
stride
=-
1
,
**
xargs
):
super
(
MaxLayer
,
self
).
__init__
(
name
,
'max'
,
0
,
inputs
=
inputs
,
**
xargs
)
config_assert
(
len
(
self
.
inputs
)
==
1
,
'MaxLayer must have 1 input'
)
if
trans_type
==
'seq'
:
config_assert
(
stride
==
-
1
,
'subseq does not support stride window'
)
self
.
config
.
trans_type
=
trans_type
self
.
config
.
seq_pool_stride
=
stride
for
input_index
in
xrange
(
len
(
self
.
inputs
)):
input_layer
=
self
.
get_input_layer
(
input_index
)
self
.
set_layer_size
(
input_layer
.
size
)
...
...
@@ -2731,11 +2735,15 @@ class AverageLayer(LayerBase):
average_strategy
=
'average'
,
trans_type
=
'non-seq'
,
bias
=
False
,
stride
=-
1
,
**
xargs
):
super
(
AverageLayer
,
self
).
__init__
(
name
,
'average'
,
0
,
inputs
=
inputs
,
**
xargs
)
self
.
config
.
average_strategy
=
average_strategy
if
trans_type
==
'seq'
:
config_assert
(
stride
==
-
1
,
'subseq does not support stride window'
)
self
.
config
.
trans_type
=
trans_type
self
.
config
.
seq_pool_stride
=
stride
config_assert
(
len
(
inputs
)
==
1
,
'AverageLayer must have 1 input'
)
for
input_index
in
xrange
(
len
(
self
.
inputs
)):
input_layer
=
self
.
get_input_layer
(
input_index
)
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
7f380c1b
...
...
@@ -1246,10 +1246,19 @@ def pooling_layer(input,
name
=
None
,
bias_attr
=
None
,
agg_level
=
AggregateLevel
.
TO_NO_SEQUENCE
,
stride
=-
1
,
layer_attr
=
None
):
"""
Pooling layer for sequence inputs, not used for Image.
If stride > 0, this layer slides a window whose size is determined by stride,
and return the pooling value of the window as the output. Thus, a long sequence
will be shorten.
The parameter stride specifies the intervals at which to apply the pooling
operation. Note that for sequence with sub-sequence, the default value
of stride is -1.
The example usage is:
.. code-block:: python
...
...
@@ -1268,6 +1277,8 @@ def pooling_layer(input,
:param pooling_type: Type of pooling, MaxPooling(default), AvgPooling,
SumPooling, SquareRootNPooling.
:type pooling_type: BasePoolingType|None
:param stride: The step size between successive pooling regions.
:type stride: Int
:param bias_attr: Bias parameter attribute. False if no bias.
:type bias_attr: ParameterAttribute|None|False
:param layer_attr: The Extra Attributes for layer, such as dropout.
...
...
@@ -1285,12 +1296,16 @@ def pooling_layer(input,
extra_dict
[
'output_max_index'
]
=
pooling_type
.
output_max_index
extra_dict
.
update
(
ExtraLayerAttribute
.
to_kwargs
(
layer_attr
))
if
agg_level
==
AggregateLevel
.
TO_SEQUENCE
:
assert
stride
==
-
1
Layer
(
name
=
name
,
type
=
pooling_type
.
name
,
inputs
=
[
Input
(
input
.
name
)],
bias
=
ParamAttr
.
to_bias
(
bias_attr
),
trans_type
=
agg_level
,
stride
=
stride
,
**
extra_dict
)
return
LayerOutput
(
...
...
@@ -1552,7 +1567,7 @@ def last_seq(input,
:type name: basestring
:param input: Input layer name.
:type input: LayerOutput
:param stride:
window size
.
:param stride:
The step size between successive pooling regions
.
:type stride: Int
:param layer_attr: extra layer attributes.
:type layer_attr: ExtraLayerAttribute.
...
...
@@ -1608,7 +1623,7 @@ def first_seq(input,
:type name: basestring
:param input: Input layer name.
:type input: LayerOutput
:param stride:
window size
.
:param stride:
The step size between successive pooling regions
.
:type stride: Int
:param layer_attr: extra layer attributes.
:type layer_attr: ExtraLayerAttribute.
...
...
python/paddle/trainer_config_helpers/tests/configs/protostr/test_sequence_pooling.protostr
浏览文件 @
7f380c1b
...
...
@@ -14,6 +14,7 @@ layers {
input_layer_name: "dat_in"
}
trans_type: "seq"
seq_pool_stride: -1
}
layers {
name: "__seq_pooling_1__"
...
...
@@ -24,6 +25,7 @@ layers {
input_layer_name: "dat_in"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__seq_pooling_2__"
...
...
@@ -35,6 +37,7 @@ layers {
}
average_strategy: "average"
trans_type: "seq"
seq_pool_stride: -1
}
layers {
name: "__seq_pooling_3__"
...
...
@@ -46,6 +49,7 @@ layers {
}
average_strategy: "average"
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__seq_pooling_4__"
...
...
@@ -57,6 +61,7 @@ layers {
}
average_strategy: "sum"
trans_type: "seq"
seq_pool_stride: -1
}
layers {
name: "__seq_pooling_5__"
...
...
@@ -68,6 +73,7 @@ layers {
}
average_strategy: "sum"
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__seq_pooling_6__"
...
...
@@ -77,8 +83,44 @@ layers {
inputs {
input_layer_name: "dat_in"
}
trans_type: "non-seq"
seq_pool_stride: 5
}
layers {
name: "__seq_pooling_7__"
type: "average"
size: 100
active_type: ""
inputs {
input_layer_name: "dat_in"
}
average_strategy: "average"
trans_type: "non-seq"
seq_pool_stride: 5
}
layers {
name: "__seq_pooling_8__"
type: "average"
size: 100
active_type: ""
inputs {
input_layer_name: "dat_in"
}
average_strategy: "sum"
trans_type: "non-seq"
seq_pool_stride: 5
}
layers {
name: "__seq_pooling_9__"
type: "max"
size: 100
active_type: ""
inputs {
input_layer_name: "dat_in"
}
output_max_index: true
trans_type: "non-seq"
seq_pool_stride: -1
}
input_layer_names: "dat_in"
output_layer_names: "__seq_pooling_0__"
...
...
@@ -88,6 +130,9 @@ output_layer_names: "__seq_pooling_3__"
output_layer_names: "__seq_pooling_4__"
output_layer_names: "__seq_pooling_5__"
output_layer_names: "__seq_pooling_6__"
output_layer_names: "__seq_pooling_7__"
output_layer_names: "__seq_pooling_8__"
output_layer_names: "__seq_pooling_9__"
sub_models {
name: "root"
layer_names: "dat_in"
...
...
@@ -98,6 +143,9 @@ sub_models {
layer_names: "__seq_pooling_4__"
layer_names: "__seq_pooling_5__"
layer_names: "__seq_pooling_6__"
layer_names: "__seq_pooling_7__"
layer_names: "__seq_pooling_8__"
layer_names: "__seq_pooling_9__"
input_layer_names: "dat_in"
output_layer_names: "__seq_pooling_0__"
output_layer_names: "__seq_pooling_1__"
...
...
@@ -106,6 +154,9 @@ sub_models {
output_layer_names: "__seq_pooling_4__"
output_layer_names: "__seq_pooling_5__"
output_layer_names: "__seq_pooling_6__"
output_layer_names: "__seq_pooling_7__"
output_layer_names: "__seq_pooling_8__"
output_layer_names: "__seq_pooling_9__"
is_recurrent_layer_group: false
}
python/paddle/trainer_config_helpers/tests/configs/test_sequence_pooling.py
浏览文件 @
7f380c1b
...
...
@@ -14,6 +14,14 @@ for pt in POOL_TYPE:
for
al
in
AGG_LEVEL
:
opts
.
append
(
pooling_layer
(
input
=
din
,
agg_level
=
al
,
pooling_type
=
pt
()))
for
pt
in
POOL_TYPE
:
opts
.
append
(
pooling_layer
(
input
=
din
,
agg_level
=
AggregateLevel
.
TO_NO_SEQUENCE
,
pooling_type
=
pt
(),
stride
=
5
))
opts
.
append
(
pooling_layer
(
input
=
din
,
pooling_type
=
MaxPooling
(
output_max_index
=
True
)))
...
...
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