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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.
...
@@ -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
See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include <set>
#include <vector>
#include <vector>
#include "paddle/math/Vector.h"
#include "paddle/math/Vector.h"
...
@@ -72,6 +73,7 @@ class ChunkEvaluator : public Evaluator {
...
@@ -72,6 +73,7 @@ class ChunkEvaluator : public Evaluator {
std
::
vector
<
Segment
>
labelSegments_
;
std
::
vector
<
Segment
>
labelSegments_
;
std
::
vector
<
Segment
>
outputSegments_
;
std
::
vector
<
Segment
>
outputSegments_
;
std
::
set
<
int
>
excludedChunkTypes_
;
public:
public:
virtual
void
init
(
const
EvaluatorConfig
&
config
)
{
virtual
void
init
(
const
EvaluatorConfig
&
config
)
{
...
@@ -105,6 +107,10 @@ public:
...
@@ -105,6 +107,10 @@ public:
}
}
CHECK
(
config
.
has_num_chunk_types
())
<<
"Missing num_chunk_types in config"
;
CHECK
(
config
.
has_num_chunk_types
())
<<
"Missing num_chunk_types in config"
;
otherChunkType_
=
numChunkTypes_
=
config
.
num_chunk_types
();
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
()
{
virtual
void
start
()
{
...
@@ -156,7 +162,8 @@ public:
...
@@ -156,7 +162,8 @@ public:
getSegments
(
label
,
length
,
labelSegments_
);
getSegments
(
label
,
length
,
labelSegments_
);
size_t
i
=
0
,
j
=
0
;
size_t
i
=
0
,
j
=
0
;
while
(
i
<
outputSegments_
.
size
()
&&
j
<
labelSegments_
.
size
())
{
while
(
i
<
outputSegments_
.
size
()
&&
j
<
labelSegments_
.
size
())
{
if
(
outputSegments_
[
i
]
==
labelSegments_
[
j
])
{
if
(
outputSegments_
[
i
]
==
labelSegments_
[
j
]
&&
excludedChunkTypes_
.
count
(
outputSegments_
[
i
].
type
)
!=
1
)
{
++
numCorrect_
;
++
numCorrect_
;
}
}
if
(
outputSegments_
[
i
].
end
<
labelSegments_
[
j
].
end
)
{
if
(
outputSegments_
[
i
].
end
<
labelSegments_
[
j
].
end
)
{
...
@@ -168,8 +175,12 @@ public:
...
@@ -168,8 +175,12 @@ public:
++
j
;
++
j
;
}
}
}
}
numLabelSegments_
+=
labelSegments_
.
size
();
for
(
auto
&
segment
:
labelSegments_
)
{
numOutputSegments_
+=
outputSegments_
.
size
();
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
)
{
void
getSegments
(
int
*
label
,
int
length
,
std
::
vector
<
Segment
>&
segments
)
{
...
...
proto/ModelConfig.proto
浏览文件 @
2965df51
...
@@ -433,8 +433,10 @@ message EvaluatorConfig {
...
@@ -433,8 +433,10 @@ message EvaluatorConfig {
repeated
string
input_layers
=
3
;
repeated
string
input_layers
=
3
;
// Used by ChunkEvaluator
// Used by ChunkEvaluator
optional
string
chunk_scheme
=
4
;
// one of "IOB", "IOE", "IOBES"
// one of "IOB", "IOE", "IOBES"
optional
int32
num_chunk_types
=
5
;
// number of chunk types other than "other"
optional
string
chunk_scheme
=
4
;
// number of chunk types other than "other"
optional
int32
num_chunk_types
=
5
;
// Used by PrecisionRecallEvaluator and ClassificationErrorEvaluator
// Used by PrecisionRecallEvaluator and ClassificationErrorEvaluator
// For multi binary labels: true if output > classification_threshold
// For multi binary labels: true if output > classification_threshold
...
@@ -453,6 +455,10 @@ message EvaluatorConfig {
...
@@ -453,6 +455,10 @@ message EvaluatorConfig {
// whether to delimit the sequence in the seq_text_printer
// whether to delimit the sequence in the seq_text_printer
optional
bool
delimited
=
11
[
default
=
true
];
optional
bool
delimited
=
11
[
default
=
true
];
// Used by ChunkEvaluator
// chunk of these types are not counted
repeated
int32
excluded_chunk_types
=
12
;
}
}
message
LinkConfig
{
message
LinkConfig
{
...
...
python/paddle/trainer/config_parser.py
浏览文件 @
2965df51
...
@@ -1240,7 +1240,8 @@ def Evaluator(
...
@@ -1240,7 +1240,8 @@ def Evaluator(
dict_file
=
None
,
dict_file
=
None
,
result_file
=
None
,
result_file
=
None
,
num_results
=
None
,
num_results
=
None
,
delimited
=
None
,
):
delimited
=
None
,
excluded_chunk_types
=
None
,
):
evaluator
=
g_config
.
model_config
.
evaluators
.
add
()
evaluator
=
g_config
.
model_config
.
evaluators
.
add
()
evaluator
.
type
=
type
evaluator
.
type
=
type
evaluator
.
name
=
MakeLayerNameInSubmodel
(
name
)
evaluator
.
name
=
MakeLayerNameInSubmodel
(
name
)
...
@@ -1269,6 +1270,9 @@ def Evaluator(
...
@@ -1269,6 +1270,9 @@ def Evaluator(
if
delimited
is
not
None
:
if
delimited
is
not
None
:
evaluator
.
delimited
=
delimited
evaluator
.
delimited
=
delimited
if
excluded_chunk_types
:
evaluator
.
excluded_chunk_types
.
extend
(
excluded_chunk_types
)
class
LayerBase
(
object
):
class
LayerBase
(
object
):
def
__init__
(
def
__init__
(
...
...
python/paddle/trainer_config_helpers/evaluators.py
浏览文件 @
2965df51
...
@@ -57,7 +57,8 @@ def evaluator(*attrs):
...
@@ -57,7 +57,8 @@ def evaluator(*attrs):
return
impl
return
impl
def
evaluator_base
(
input
,
def
evaluator_base
(
input
,
type
,
type
,
label
=
None
,
label
=
None
,
weight
=
None
,
weight
=
None
,
...
@@ -69,7 +70,8 @@ def evaluator_base(input,
...
@@ -69,7 +70,8 @@ def evaluator_base(input,
dict_file
=
None
,
dict_file
=
None
,
result_file
=
None
,
result_file
=
None
,
num_results
=
None
,
num_results
=
None
,
delimited
=
None
):
delimited
=
None
,
excluded_chunk_types
=
None
,
):
"""
"""
Evaluator will evaluate the network status while training/testing.
Evaluator will evaluate the network status while training/testing.
...
@@ -127,7 +129,8 @@ def evaluator_base(input,
...
@@ -127,7 +129,8 @@ def evaluator_base(input,
positive_label
=
positive_label
,
positive_label
=
positive_label
,
dict_file
=
dict_file
,
dict_file
=
dict_file
,
result_file
=
result_file
,
result_file
=
result_file
,
delimited
=
delimited
)
delimited
=
delimited
,
excluded_chunk_types
=
excluded_chunk_types
,
)
@
evaluator
(
EvaluatorAttribute
.
FOR_CLASSIFICATION
)
@
evaluator
(
EvaluatorAttribute
.
FOR_CLASSIFICATION
)
...
@@ -330,7 +333,8 @@ def chunk_evaluator(
...
@@ -330,7 +333,8 @@ def chunk_evaluator(
label
,
label
,
chunk_scheme
,
chunk_scheme
,
num_chunk_types
,
num_chunk_types
,
name
=
None
,
):
name
=
None
,
excluded_chunk_types
=
None
,
):
"""
"""
Chunk evaluator is used to evaluate segment labelling accuracy for a
Chunk evaluator is used to evaluate segment labelling accuracy for a
sequence. It calculates the chunk detection F1 score.
sequence. It calculates the chunk detection F1 score.
...
@@ -376,6 +380,8 @@ def chunk_evaluator(
...
@@ -376,6 +380,8 @@ def chunk_evaluator(
:param num_chunk_types: number of chunk types other than "other"
:param num_chunk_types: number of chunk types other than "other"
:param name: The Evaluator name, it is optional.
:param name: The Evaluator name, it is optional.
:type name: basename|None
: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
(
evaluator_base
(
name
=
name
,
name
=
name
,
...
@@ -383,7 +389,8 @@ def chunk_evaluator(
...
@@ -383,7 +389,8 @@ def chunk_evaluator(
input
=
input
,
input
=
input
,
label
=
label
,
label
=
label
,
chunk_scheme
=
chunk_scheme
,
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
)
@
evaluator
(
EvaluatorAttribute
.
FOR_UTILS
)
...
...
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