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9298a9ec
编写于
3月 24, 2017
作者:
L
Luo Tao
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
stride pooling for seqlastin and seqfirstin
上级
bfc33108
变更
17
隐藏空白更改
内联
并排
Showing
17 changed file
with
235 addition
and
19 deletion
+235
-19
paddle/gserver/layers/SequenceLastInstanceLayer.cpp
paddle/gserver/layers/SequenceLastInstanceLayer.cpp
+14
-9
paddle/gserver/layers/SequencePoolLayer.cpp
paddle/gserver/layers/SequencePoolLayer.cpp
+9
-2
paddle/gserver/layers/SequencePoolLayer.h
paddle/gserver/layers/SequencePoolLayer.h
+7
-0
paddle/gserver/tests/test_LayerGrad.cpp
paddle/gserver/tests/test_LayerGrad.cpp
+13
-3
paddle/parameter/Argument.cpp
paddle/parameter/Argument.cpp
+40
-0
paddle/parameter/Argument.h
paddle/parameter/Argument.h
+8
-0
paddle/parameter/tests/CMakeLists.txt
paddle/parameter/tests/CMakeLists.txt
+1
-0
paddle/parameter/tests/test_argument.cpp
paddle/parameter/tests/test_argument.cpp
+52
-0
proto/ModelConfig.proto
proto/ModelConfig.proto
+5
-0
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+13
-5
python/paddle/trainer_config_helpers/layers.py
python/paddle/trainer_config_helpers/layers.py
+21
-0
python/paddle/trainer_config_helpers/tests/configs/last_first_seq.py
...le/trainer_config_helpers/tests/configs/last_first_seq.py
+3
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/last_first_seq.protostr
...ig_helpers/tests/configs/protostr/last_first_seq.protostr
+33
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/shared_gru.protostr
...config_helpers/tests/configs/protostr/shared_gru.protostr
+2
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/shared_lstm.protostr
...onfig_helpers/tests/configs/protostr/shared_lstm.protostr
+2
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/simple_rnn_layers.protostr
...helpers/tests/configs/protostr/simple_rnn_layers.protostr
+6
-0
python/paddle/trainer_config_helpers/tests/configs/protostr/test_rnn_group.protostr
...ig_helpers/tests/configs/protostr/test_rnn_group.protostr
+6
-0
未找到文件。
paddle/gserver/layers/SequenceLastInstanceLayer.cpp
浏览文件 @
9298a9ec
...
...
@@ -25,6 +25,9 @@ namespace paddle {
* Input: a sequence
* If SequenceLevel = kNonseq:
* Output: a sequence containing only the last instance of the input sequence
* If stride_ > 0:
* Output: a shorten sequence containing several last instances of the
* input sequence with stride window.
* If SequenceLevel = kSeq:
* Check input sequence must has sub-sequence
* Output: a sequence containing only the last instance of each sub-sequence
...
...
@@ -37,6 +40,8 @@ class SequenceLastInstanceLayer : public SequencePoolLayer {
protected:
MatrixPtr
tmpSrc_
;
MatrixPtr
tmpDest_
;
bool
select_first_
;
std
::
vector
<
int
>
insId_
;
public:
explicit
SequenceLastInstanceLayer
(
const
LayerConfig
&
config
)
...
...
@@ -54,6 +59,7 @@ REGISTER_LAYER(seqlastins, SequenceLastInstanceLayer);
bool
SequenceLastInstanceLayer
::
init
(
const
LayerMap
&
layerMap
,
const
ParameterMap
&
parameterMap
)
{
SequencePoolLayer
::
init
(
layerMap
,
parameterMap
);
select_first_
=
config_
.
select_first
();
tmpSrc_
=
Matrix
::
create
(
nullptr
,
/* height= */
1
,
1
,
/* trans= */
false
,
useGpu_
);
...
...
@@ -74,9 +80,13 @@ void SequenceLastInstanceLayer::forward(PassType passType) {
AsyncGpuBlock
asyncGpuBlock
;
REGISTER_TIMER_INFO
(
"SequenceLastInstanceLayerForward"
,
getName
().
c_str
());
insId_
.
clear
();
for
(
size_t
seqId
=
0
;
seqId
<
newBatchSize_
;
++
seqId
)
{
int
insId
=
config_
.
select_first
()
?
starts
[
seqId
]
:
starts
[
seqId
+
1
]
-
1
;
int
insId
=
(
stride_
>
0
)
?
(
select_first_
?
stridePositions_
[
seqId
]
:
stridePositions_
[
seqId
+
1
]
-
1
)
:
(
select_first_
?
starts
[
seqId
]
:
starts
[
seqId
+
1
]
-
1
);
insId_
.
push_back
(
insId
);
outputValue
->
subMatrix
(
seqId
,
1
,
tmpDest_
)
->
assign
(
*
(
inputValue
->
subMatrix
(
insId
,
1
,
tmpSrc_
)));
...
...
@@ -96,18 +106,13 @@ void SequenceLastInstanceLayer::backward(const UpdateCallback& callback) {
MatrixPtr
inputGrad
=
getInputGrad
(
0
);
MatrixPtr
outputGrad
=
getOutputGrad
();
const
int
*
starts
=
startPositions_
->
getData
(
false
);
size_t
numSequences
=
startPositions_
->
getSize
()
-
1
;
if
(
inputGrad
)
{
AsyncGpuBlock
asyncGpuBlock
;
REGISTER_TIMER_INFO
(
"SequenceLastInstanceLayerBackward"
,
getName
().
c_str
());
for
(
size_t
seqId
=
0
;
seqId
<
numSequences
;
++
seqId
)
{
int
insId
=
config_
.
select_first
()
?
starts
[
seqId
]
:
starts
[
seqId
+
1
]
-
1
;
inputGrad
->
subMatrix
(
insId
,
1
,
tmpDest_
)
for
(
size_t
seqId
=
0
;
seqId
<
newBatchSize_
;
++
seqId
)
{
inputGrad
->
subMatrix
(
insId_
[
seqId
],
1
,
tmpDest_
)
->
add
(
*
(
outputGrad
->
subMatrix
(
seqId
,
1
,
tmpSrc_
)));
}
}
...
...
paddle/gserver/layers/SequencePoolLayer.cpp
浏览文件 @
9298a9ec
...
...
@@ -37,6 +37,7 @@ bool SequencePoolLayer::init(const LayerMap& layerMap,
}
else
{
LOG
(
FATAL
)
<<
"Unknown trans_type: "
<<
config_
.
trans_type
();
}
stride_
=
config_
.
seq_pool_stride
();
setNeedSequenceInfo
(
false
);
return
true
;
}
...
...
@@ -55,8 +56,6 @@ void SequencePoolLayer::forward(PassType passType) {
CHECK_EQ
(
starts
->
getData
()[
newBatchSize_
],
input
.
getBatchSize
());
CHECK_EQ
(
newBatchSize_
,
starts
->
getSize
()
-
1
);
resetOutput
(
newBatchSize_
,
dim
);
/* If type_ = kNonSeq, both seq has or not has sub-seq degrade to a non-seq,
* thus, in this case, output_ has no sequenceStartPositions.
* If type_ = kSeq, seq has sub-seq degrades to a seq, thus, only in this
...
...
@@ -67,6 +66,14 @@ void SequencePoolLayer::forward(PassType passType) {
<<
"when trans_type = seq, input must hasSubseq"
;
output_
.
degradeSequence
(
input
);
}
if
(
stride_
>
0
)
{
CHECK_EQ
(
input
.
hasSubseq
(),
0UL
)
<<
"sequence stride pooling is not suitable for hasSubseq now"
;
output_
.
poolSequenceWithStride
(
input
,
stride_
,
&
stridePositions_
);
newBatchSize_
=
stridePositions_
.
size
()
-
1
;
}
resetOutput
(
newBatchSize_
,
dim
);
}
void
SequencePoolLayer
::
backward
(
const
UpdateCallback
&
callback
)
{
...
...
paddle/gserver/layers/SequencePoolLayer.h
浏览文件 @
9298a9ec
...
...
@@ -26,6 +26,10 @@ namespace paddle {
* Output: output size is the number of input sequences (NOT input instances)
* output[i] = seqlastin/average/max_{for each instance in this
* sequence}{input[i]}
* If stride_ > 0:
* Check input sequence must don't have sub-sequence
* Output: a shorten sequence, pooling is performed upon a small local
* area
* If SequenceLevel = kSeq:
* Check input sequence must has sub-sequence
* Output: output size is the number of input sub-sequences
...
...
@@ -42,6 +46,9 @@ protected:
enum
SequenceLevel
{
kNonSeq
=
0
,
kSeq
=
1
};
size_t
newBatchSize_
;
ICpuGpuVectorPtr
startPositions_
;
int
stride_
;
// store the start position of each stride window
std
::
vector
<
int
>
stridePositions_
;
public:
explicit
SequencePoolLayer
(
const
LayerConfig
&
config
)
:
Layer
(
config
)
{}
...
...
paddle/gserver/tests/test_LayerGrad.cpp
浏览文件 @
9298a9ec
...
...
@@ -804,10 +804,14 @@ TEST(Layer, ExpandLayer) {
testExpandLayer
(
"seq"
,
true
);
// seq expand to hasSubseq
}
void
testDegradeLayer
(
bool
hasSubseq
,
string
layer_type
,
string
trans_type
)
{
void
testDegradeLayer
(
bool
hasSubseq
,
string
layer_type
,
string
trans_type
,
int
stride
=
-
1
)
{
TestConfig
config
;
config
.
layerConfig
.
set_type
(
layer_type
);
config
.
layerConfig
.
set_size
(
10
);
config
.
layerConfig
.
set_seq_pool_stride
(
stride
);
config
.
biasSize
=
0
;
config
.
inputDefs
.
push_back
(
...
...
@@ -827,12 +831,14 @@ void testDegradeLayer(bool hasSubseq, string layer_type, string trans_type) {
if
(
layer_type
==
"average"
)
{
for
(
auto
strategy
:
{
"average"
,
"sum"
,
"squarerootn"
})
{
LOG
(
INFO
)
<<
" hasSubseq="
<<
hasSubseq
<<
" trans_type="
<<
trans_type
<<
" average_strategy="
<<
strategy
;
<<
" average_strategy="
<<
strategy
<<
" seq_pool_stride="
<<
stride
;
config
.
layerConfig
.
set_average_strategy
(
strategy
);
testDegradeLayerGrad
(
config
,
layer_type
);
}
}
else
{
LOG
(
INFO
)
<<
" hasSubseq="
<<
hasSubseq
<<
" trans_type="
<<
trans_type
;
LOG
(
INFO
)
<<
" hasSubseq="
<<
hasSubseq
<<
" trans_type="
<<
trans_type
<<
" seq_pool_stride="
<<
stride
;
testDegradeLayerGrad
(
config
,
layer_type
);
}
}
...
...
@@ -847,6 +853,10 @@ TEST(Layer, SequenceLastInstanceLayer) {
testDegradeLayer
(
false
,
"seqlastins"
,
"non-seq"
);
// seq seqlastins to non-seq
testDegradeLayer
(
false
,
"seqlastins"
,
"non-seq"
,
5
);
// seq seqlastins to a shorten seq, stride window = 5
testDegradeLayer
(
true
,
"seqlastins"
,
"non-seq"
);
// hasSubseq seqlastins to non-seq
...
...
paddle/parameter/Argument.cpp
浏览文件 @
9298a9ec
...
...
@@ -559,6 +559,46 @@ void Argument::degradeSequence(const Argument& input) {
tgtBuf
[
numSequences
]
=
numSubSequences
;
}
void
Argument
::
poolSequenceWithStride
(
const
Argument
&
input
,
size_t
stride
,
std
::
vector
<
int
>*
stridePostions
)
{
/*
* If input.sequenceStartPositions = [0, 9, 14, 17, 30] and stride = 5,
* then sequenceStartPositions = [0, 2, 3, 4, 7],
* and stridePostions = [0, 5, 9, 14, 17, 22, 27, 30]
*/
CHECK
(
input
.
sequenceStartPositions
);
CHECK_EQ
(
input
.
hasSubseq
(),
0UL
);
CHECK_GT
(
stride
,
0
)
<<
"stride must larger than 0"
;
size_t
numSequences
=
input
.
getNumSequences
();
ICpuGpuVector
::
resizeOrCreate
(
sequenceStartPositions
,
numSequences
+
1
,
false
);
const
int
*
starts
=
input
.
sequenceStartPositions
->
getData
(
false
);
int
*
tgtBuf
=
sequenceStartPositions
->
getMutableData
(
false
);
// first index of target sequence and stride positions are both 0
tgtBuf
[
0
]
=
0
;
(
*
stridePostions
).
clear
();
for
(
size_t
seqId
=
0
;
seqId
<
numSequences
;
++
seqId
)
{
size_t
seqLength
=
starts
[
seqId
+
1
]
-
starts
[
seqId
];
(
*
stridePostions
).
emplace_back
(
starts
[
seqId
]);
if
(
seqLength
==
0
)
{
// empty sequence
tgtBuf
[
seqId
+
1
]
=
tgtBuf
[
seqId
];
}
else
if
(
seqLength
<
stride
)
{
tgtBuf
[
seqId
+
1
]
=
tgtBuf
[
seqId
]
+
1
;
}
else
{
tgtBuf
[
seqId
+
1
]
=
tgtBuf
[
seqId
]
+
ceil
((
float
)
seqLength
/
stride
);
int
size
=
(
seqLength
%
stride
)
?
seqLength
/
stride
:
seqLength
/
stride
-
1
;
for
(
int
i
=
0
;
i
<
size
;
i
++
)
{
(
*
stridePostions
).
emplace_back
((
*
stridePostions
).
back
()
+
stride
);
}
}
}
(
*
stridePostions
).
emplace_back
(
starts
[
numSequences
]);
CHECK_EQ
((
*
stridePostions
).
size
()
-
1
,
tgtBuf
[
numSequences
]);
}
void
Argument
::
getValueString
(
std
::
unordered_map
<
std
::
string
,
std
::
string
>*
out
)
const
{
if
(
value
)
{
...
...
paddle/parameter/Argument.h
浏览文件 @
9298a9ec
...
...
@@ -291,6 +291,14 @@ struct Argument {
*/
void
degradeSequence
(
const
Argument
&
input
);
/*
After pooling with stride n (n is smaller than sequence length),
a long sequence will be shorten.
This function is not suitable for sequence with sub-sequence now.
*/
void
poolSequenceWithStride
(
const
Argument
&
input
,
size_t
stride
,
std
::
vector
<
int
>*
stridePositions
);
/**
* @brief getValueString will return the argument's output in string. There
* are several kinds of output. The keys of output dictionary are 'value',
...
...
paddle/parameter/tests/CMakeLists.txt
浏览文件 @
9298a9ec
add_simple_unittest
(
test_common
)
add_simple_unittest
(
test_argument
)
paddle/parameter/tests/test_argument.cpp
0 → 100644
浏览文件 @
9298a9ec
/* 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 <gtest/gtest.h>
#include <paddle/parameter/Argument.h>
using
namespace
paddle
;
// NOLINT
TEST
(
Argument
,
poolSequenceWithStride
)
{
Argument
input
,
output
;
ICpuGpuVector
::
resizeOrCreate
(
input
.
sequenceStartPositions
,
5
,
false
);
int
*
inStart
=
input
.
sequenceStartPositions
->
getMutableData
(
false
);
inStart
[
0
]
=
0
;
inStart
[
1
]
=
9
;
inStart
[
2
]
=
14
;
inStart
[
3
]
=
17
;
inStart
[
4
]
=
30
;
std
::
vector
<
int
>
stridePositions
;
stridePositions
.
clear
();
output
.
poolSequenceWithStride
(
input
,
5
/* stride */
,
&
stridePositions
);
const
int
*
outStart
=
output
.
sequenceStartPositions
->
getData
(
false
);
CHECK_EQ
(
outStart
[
0
],
0
);
CHECK_EQ
(
outStart
[
1
],
2
);
CHECK_EQ
(
outStart
[
2
],
3
);
CHECK_EQ
(
outStart
[
3
],
4
);
CHECK_EQ
(
outStart
[
4
],
7
);
CHECK_EQ
(
stridePositions
.
size
(),
8
);
int
strideResult
[]
=
{
0
,
5
,
9
,
14
,
17
,
22
,
27
,
30
};
for
(
int
i
=
0
;
i
<
8
;
i
++
)
{
CHECK_EQ
(
stridePositions
[
i
],
strideResult
[
i
]);
}
}
int
main
(
int
argc
,
char
**
argv
)
{
testing
::
InitGoogleTest
(
&
argc
,
argv
);
initMain
(
argc
,
argv
);
return
RUN_ALL_TESTS
();
}
proto/ModelConfig.proto
浏览文件 @
9298a9ec
...
...
@@ -441,6 +441,11 @@ message LayerConfig {
// blank label used in ctc loss
optional
uint32
blank
=
52
[
default
=
0
];
// stride parameter for seqlastins layer, AverageLayer, MaxLayer, which
// controls the scope of pooling operation. can be set > 0.
// leave empty or set to -1 to disable this stride pooling.
optional
int32
seq_pool_stride
=
53
[
default
=
-
1
];
}
message
EvaluatorConfig
{
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
9298a9ec
...
...
@@ -2480,6 +2480,7 @@ class SequenceLastInstanceLayer(LayerBase):
active_type
=
'linear'
,
trans_type
=
'non-seq'
,
bias
=
False
,
stride
=-
1
,
**
xargs
):
super
(
SequenceLastInstanceLayer
,
self
).
__init__
(
name
,
...
...
@@ -2490,10 +2491,11 @@ class SequenceLastInstanceLayer(LayerBase):
**
xargs
)
config_assert
(
len
(
inputs
)
==
1
,
'SequenceLastInstanceLayer must have 1 input'
)
if
trans_type
==
'seq'
:
config_assert
(
stride
==
-
1
,
'subseq do not support stride window'
)
self
.
config
.
trans_type
=
trans_type
for
input_index
in
xrange
(
len
(
self
.
inputs
)):
input_layer
=
self
.
get_input_layer
(
input_index
)
self
.
set_layer_size
(
input_layer
.
size
)
self
.
config
.
seq_pool_stride
=
stride
self
.
set_layer_size
(
self
.
get_input_layer
(
0
).
size
)
self
.
create_bias_parameter
(
bias
,
self
.
config
.
size
)
...
...
@@ -2505,10 +2507,16 @@ class SequenceFirstInstanceLayer(SequenceLastInstanceLayer):
active_type
=
'linear'
,
trans_type
=
'non-seq'
,
bias
=
False
,
stride
=-
1
,
**
xargs
):
super
(
SequenceFirstInstanceLayer
,
self
).
__init__
(
name
,
inputs
=
inputs
,
active_type
=
active_type
,
bias
=
bias
,
**
xargs
)
self
.
config
.
trans_type
=
trans_type
name
,
inputs
=
inputs
,
active_type
=
active_type
,
trans_type
=
trans_type
,
bias
=
bias
,
stride
=
stride
,
**
xargs
)
self
.
config
.
select_first
=
True
...
...
python/paddle/trainer_config_helpers/layers.py
浏览文件 @
9298a9ec
...
...
@@ -1301,10 +1301,15 @@ def grumemory(input,
def
last_seq
(
input
,
name
=
None
,
agg_level
=
AggregateLevel
.
EACH_TIMESTEP
,
stride
=-
1
,
layer_attr
=
None
):
"""
Get Last Timestamp Activation of a sequence.
If stride > 0, get last timestamp upon a stride window of sequence.
And a long sequence will be shorten. Note that for sequence with
sub-sequence, stride is default -1 now.
The simple usage is:
.. code-block:: python
...
...
@@ -1316,6 +1321,8 @@ def last_seq(input,
:type name: basestring
:param input: Input layer name.
:type input: LayerOutput
:param stride: parameter of stride window.
:type stride: Int
:param layer_attr: extra layer attributes.
:type layer_attr: ExtraLayerAttribute.
:return: LayerOutput object.
...
...
@@ -1327,11 +1334,15 @@ def last_seq(input,
" series information at all. Maybe you want to use"
" first_seq instead."
)
if
agg_level
==
AggregateLevel
.
EACH_SEQUENCE
:
assert
stride
==
-
1
Layer
(
name
=
name
,
type
=
LayerType
.
SEQUENCE_LAST_INSTANCE
,
inputs
=
[
input
.
name
],
trans_type
=
agg_level
,
stride
=
stride
,
**
ExtraLayerAttribute
.
to_kwargs
(
layer_attr
))
return
LayerOutput
(
name
,
...
...
@@ -1345,10 +1356,16 @@ def last_seq(input,
def
first_seq
(
input
,
name
=
None
,
agg_level
=
AggregateLevel
.
EACH_TIMESTEP
,
stride
=-
1
,
layer_attr
=
None
):
"""
Get First Timestamp Activation of a sequence.
If stride > 0, get first timestamp upon a stride window of sequence,
and a long sequence will be shorten. Note that for sequence with
sub-sequence, stride is default -1 now.
The simple usage is:
.. code-block:: python
...
...
@@ -1372,11 +1389,15 @@ def first_seq(input,
' time series information at all. Maybe you want to use'
' last_seq instead.'
)
if
agg_level
==
AggregateLevel
.
EACH_SEQUENCE
:
assert
stride
==
-
1
Layer
(
name
=
name
,
type
=
LayerType
.
SEQUENCE_FIRST_INSTANCE
,
inputs
=
[
input
.
name
],
trans_type
=
agg_level
,
stride
=
stride
,
**
ExtraLayerAttribute
.
to_kwargs
(
layer_attr
))
return
LayerOutput
(
name
,
...
...
python/paddle/trainer_config_helpers/tests/configs/last_first_seq.py
浏览文件 @
9298a9ec
...
...
@@ -14,4 +14,7 @@ for op in seq_op:
for
al
in
agg_level
:
opts
.
append
(
op
(
input
=
din
,
agg_level
=
al
))
for
op
in
seq_op
:
opts
.
append
(
op
(
input
=
din
,
agg_level
=
AggregateLevel
.
EACH_TIMESTEP
,
stride
=
5
))
outputs
(
opts
)
python/paddle/trainer_config_helpers/tests/configs/protostr/last_first_seq.protostr
浏览文件 @
9298a9ec
...
...
@@ -15,6 +15,7 @@ layers {
}
select_first: true
trans_type: "seq"
seq_pool_stride: -1
}
layers {
name: "__first_seq_1__"
...
...
@@ -26,6 +27,7 @@ layers {
}
select_first: true
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__last_seq_0__"
...
...
@@ -36,6 +38,7 @@ layers {
input_layer_name: "data"
}
trans_type: "seq"
seq_pool_stride: -1
}
layers {
name: "__last_seq_1__"
...
...
@@ -46,12 +49,38 @@ layers {
input_layer_name: "data"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__first_seq_2__"
type: "seqlastins"
size: 30
active_type: "linear"
inputs {
input_layer_name: "data"
}
select_first: true
trans_type: "non-seq"
seq_pool_stride: 5
}
layers {
name: "__last_seq_2__"
type: "seqlastins"
size: 30
active_type: "linear"
inputs {
input_layer_name: "data"
}
trans_type: "non-seq"
seq_pool_stride: 5
}
input_layer_names: "data"
output_layer_names: "__first_seq_0__"
output_layer_names: "__first_seq_1__"
output_layer_names: "__last_seq_0__"
output_layer_names: "__last_seq_1__"
output_layer_names: "__first_seq_2__"
output_layer_names: "__last_seq_2__"
sub_models {
name: "root"
layer_names: "data"
...
...
@@ -59,11 +88,15 @@ sub_models {
layer_names: "__first_seq_1__"
layer_names: "__last_seq_0__"
layer_names: "__last_seq_1__"
layer_names: "__first_seq_2__"
layer_names: "__last_seq_2__"
input_layer_names: "data"
output_layer_names: "__first_seq_0__"
output_layer_names: "__first_seq_1__"
output_layer_names: "__last_seq_0__"
output_layer_names: "__last_seq_1__"
output_layer_names: "__first_seq_2__"
output_layer_names: "__last_seq_2__"
is_recurrent_layer_group: false
}
python/paddle/trainer_config_helpers/tests/configs/protostr/shared_gru.protostr
浏览文件 @
9298a9ec
...
...
@@ -128,6 +128,7 @@ layers {
input_layer_name: "__simple_gru_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__last_seq_1__"
...
...
@@ -138,6 +139,7 @@ layers {
input_layer_name: "__simple_gru_1__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__fc_layer_0__"
...
...
python/paddle/trainer_config_helpers/tests/configs/protostr/shared_lstm.protostr
浏览文件 @
9298a9ec
...
...
@@ -210,6 +210,7 @@ layers {
input_layer_name: "__lstm_group_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__last_seq_1__"
...
...
@@ -220,6 +221,7 @@ layers {
input_layer_name: "__lstm_group_1__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__fc_layer_0__"
...
...
python/paddle/trainer_config_helpers/tests/configs/protostr/simple_rnn_layers.protostr
浏览文件 @
9298a9ec
...
...
@@ -143,6 +143,7 @@ layers {
input_layer_name: "__recurrent_layer_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__first_seq_0__"
...
...
@@ -154,6 +155,7 @@ layers {
}
select_first: true
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__last_seq_1__"
...
...
@@ -164,6 +166,7 @@ layers {
input_layer_name: "__lstmemory_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__first_seq_1__"
...
...
@@ -175,6 +178,7 @@ layers {
}
select_first: true
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__last_seq_2__"
...
...
@@ -185,6 +189,7 @@ layers {
input_layer_name: "__gru_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__first_seq_2__"
...
...
@@ -196,6 +201,7 @@ layers {
}
select_first: true
trans_type: "non-seq"
seq_pool_stride: -1
}
parameters {
name: "___fc_layer_0__.w0"
...
...
python/paddle/trainer_config_helpers/tests/configs/protostr/test_rnn_group.protostr
浏览文件 @
9298a9ec
...
...
@@ -96,6 +96,7 @@ layers {
input_layer_name: "rnn_forward"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__recurrent_group_1__"
...
...
@@ -145,6 +146,7 @@ layers {
}
select_first: true
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__recurrent_group_2__"
...
...
@@ -193,6 +195,7 @@ layers {
input_layer_name: "rnn_subseq_forward"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__lstm_group_0___recurrent_group"
...
...
@@ -282,6 +285,7 @@ layers {
input_layer_name: "__lstm_group_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__gru_group_0___recurrent_group"
...
...
@@ -330,6 +334,7 @@ layers {
input_layer_name: "__gru_group_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
layers {
name: "__recurrent_group_3__"
...
...
@@ -378,6 +383,7 @@ layers {
input_layer_name: "__fc_layer_0__"
}
trans_type: "non-seq"
seq_pool_stride: -1
}
parameters {
name: "___mixed_0__.w0"
...
...
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