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2965df51
编写于
12月 20, 2016
作者:
P
Peng LI
提交者:
GitHub
12月 20, 2016
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差异文件
Merge pull request #960 from pengli09/chunk_evaluator
Add excluded_chunk_types to ChunkEvaluator
上级
8a42a549
6e405a10
变更
4
显示空白变更内容
内联
并排
Showing
4 changed file
with
50 addition
and
22 deletion
+50
-22
paddle/gserver/evaluators/ChunkEvaluator.cpp
paddle/gserver/evaluators/ChunkEvaluator.cpp
+14
-3
proto/ModelConfig.proto
proto/ModelConfig.proto
+8
-2
python/paddle/trainer/config_parser.py
python/paddle/trainer/config_parser.py
+5
-1
python/paddle/trainer_config_helpers/evaluators.py
python/paddle/trainer_config_helpers/evaluators.py
+23
-16
未找到文件。
paddle/gserver/evaluators/ChunkEvaluator.cpp
浏览文件 @
2965df51
...
...
@@ -12,6 +12,7 @@ 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 <set>
#include <vector>
#include "paddle/math/Vector.h"
...
...
@@ -72,6 +73,7 @@ class ChunkEvaluator : public Evaluator {
std
::
vector
<
Segment
>
labelSegments_
;
std
::
vector
<
Segment
>
outputSegments_
;
std
::
set
<
int
>
excludedChunkTypes_
;
public:
virtual
void
init
(
const
EvaluatorConfig
&
config
)
{
...
...
@@ -105,6 +107,10 @@ public:
}
CHECK
(
config
.
has_num_chunk_types
())
<<
"Missing num_chunk_types in config"
;
otherChunkType_
=
numChunkTypes_
=
config
.
num_chunk_types
();
// the chunks of types in excludedChunkTypes_ will not be counted
auto
&
tmp
=
config
.
excluded_chunk_types
();
excludedChunkTypes_
.
insert
(
tmp
.
begin
(),
tmp
.
end
());
}
virtual
void
start
()
{
...
...
@@ -156,7 +162,8 @@ public:
getSegments
(
label
,
length
,
labelSegments_
);
size_t
i
=
0
,
j
=
0
;
while
(
i
<
outputSegments_
.
size
()
&&
j
<
labelSegments_
.
size
())
{
if
(
outputSegments_
[
i
]
==
labelSegments_
[
j
])
{
if
(
outputSegments_
[
i
]
==
labelSegments_
[
j
]
&&
excludedChunkTypes_
.
count
(
outputSegments_
[
i
].
type
)
!=
1
)
{
++
numCorrect_
;
}
if
(
outputSegments_
[
i
].
end
<
labelSegments_
[
j
].
end
)
{
...
...
@@ -168,8 +175,12 @@ public:
++
j
;
}
}
numLabelSegments_
+=
labelSegments_
.
size
();
numOutputSegments_
+=
outputSegments_
.
size
();
for
(
auto
&
segment
:
labelSegments_
)
{
if
(
excludedChunkTypes_
.
count
(
segment
.
type
)
!=
1
)
++
numLabelSegments_
;
}
for
(
auto
&
segment
:
outputSegments_
)
{
if
(
excludedChunkTypes_
.
count
(
segment
.
type
)
!=
1
)
++
numOutputSegments_
;
}
}
void
getSegments
(
int
*
label
,
int
length
,
std
::
vector
<
Segment
>&
segments
)
{
...
...
proto/ModelConfig.proto
浏览文件 @
2965df51
...
...
@@ -433,8 +433,10 @@ message EvaluatorConfig {
repeated
string
input_layers
=
3
;
// Used by ChunkEvaluator
optional
string
chunk_scheme
=
4
;
// one of "IOB", "IOE", "IOBES"
optional
int32
num_chunk_types
=
5
;
// number of chunk types other than "other"
// one of "IOB", "IOE", "IOBES"
optional
string
chunk_scheme
=
4
;
// number of chunk types other than "other"
optional
int32
num_chunk_types
=
5
;
// Used by PrecisionRecallEvaluator and ClassificationErrorEvaluator
// For multi binary labels: true if output > classification_threshold
...
...
@@ -453,6 +455,10 @@ message EvaluatorConfig {
// whether to delimit the sequence in the seq_text_printer
optional
bool
delimited
=
11
[
default
=
true
];
// Used by ChunkEvaluator
// chunk of these types are not counted
repeated
int32
excluded_chunk_types
=
12
;
}
message
LinkConfig
{
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
2965df51
...
...
@@ -1240,7 +1240,8 @@ def Evaluator(
dict_file
=
None
,
result_file
=
None
,
num_results
=
None
,
delimited
=
None
,
):
delimited
=
None
,
excluded_chunk_types
=
None
,
):
evaluator
=
g_config
.
model_config
.
evaluators
.
add
()
evaluator
.
type
=
type
evaluator
.
name
=
MakeLayerNameInSubmodel
(
name
)
...
...
@@ -1269,6 +1270,9 @@ def Evaluator(
if
delimited
is
not
None
:
evaluator
.
delimited
=
delimited
if
excluded_chunk_types
:
evaluator
.
excluded_chunk_types
.
extend
(
excluded_chunk_types
)
class
LayerBase
(
object
):
def
__init__
(
...
...
python/paddle/trainer_config_helpers/evaluators.py
浏览文件 @
2965df51
...
...
@@ -57,7 +57,8 @@ def evaluator(*attrs):
return
impl
def
evaluator_base
(
input
,
def
evaluator_base
(
input
,
type
,
label
=
None
,
weight
=
None
,
...
...
@@ -69,7 +70,8 @@ def evaluator_base(input,
dict_file
=
None
,
result_file
=
None
,
num_results
=
None
,
delimited
=
None
):
delimited
=
None
,
excluded_chunk_types
=
None
,
):
"""
Evaluator will evaluate the network status while training/testing.
...
...
@@ -127,7 +129,8 @@ def evaluator_base(input,
positive_label
=
positive_label
,
dict_file
=
dict_file
,
result_file
=
result_file
,
delimited
=
delimited
)
delimited
=
delimited
,
excluded_chunk_types
=
excluded_chunk_types
,
)
@
evaluator
(
EvaluatorAttribute
.
FOR_CLASSIFICATION
)
...
...
@@ -330,7 +333,8 @@ def chunk_evaluator(
label
,
chunk_scheme
,
num_chunk_types
,
name
=
None
,
):
name
=
None
,
excluded_chunk_types
=
None
,
):
"""
Chunk evaluator is used to evaluate segment labelling accuracy for a
sequence. It calculates the chunk detection F1 score.
...
...
@@ -376,6 +380,8 @@ def chunk_evaluator(
:param num_chunk_types: number of chunk types other than "other"
:param name: The Evaluator name, it is optional.
:type name: basename|None
:param excluded_chunk_types: chunks of these types are not considered
:type excluded_chunk_types: list of integer|None
"""
evaluator_base
(
name
=
name
,
...
...
@@ -383,7 +389,8 @@ def chunk_evaluator(
input
=
input
,
label
=
label
,
chunk_scheme
=
chunk_scheme
,
num_chunk_types
=
num_chunk_types
)
num_chunk_types
=
num_chunk_types
,
excluded_chunk_types
=
excluded_chunk_types
,
)
@
evaluator
(
EvaluatorAttribute
.
FOR_UTILS
)
...
...
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