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Fix set_features on tagger

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This commit is contained in:
Matthew Honnibal 2016-08-29 14:25:22 +02:00
parent 0c7520dbb7
commit 52d2702782
2 changed files with 13 additions and 11 deletions
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4
spacy/tagger.pxd
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@ -1,13 +1,13 @@
from thinc.linear.avgtron cimport AveragedPerceptron from thinc.linear.avgtron cimport AveragedPerceptron
from thinc.extra.eg cimport Example from thinc.extra.eg cimport Example
from thinc.structs cimport ExampleC from thinc.structs cimport ExampleC, FeatureC
from .structs cimport TokenC from .structs cimport TokenC
from .vocab cimport Vocab from .vocab cimport Vocab
cdef class TaggerModel(AveragedPerceptron): cdef class TaggerModel(AveragedPerceptron):
cdef void set_featuresC(self, ExampleC* eg, const void* _token) nogil cdef int set_featuresC(self, FeatureC* feats, const void* _token) nogil
cdef class Tagger: cdef class Tagger:

20
spacy/tagger.pyx
View File

@ -71,15 +71,17 @@ cpdef enum:
cdef class TaggerModel(AveragedPerceptron): cdef class TaggerModel(AveragedPerceptron):
cdef void set_featuresC(self, ExampleC* eg, const void* _token) nogil: cdef int set_featuresC(self, FeatureC* features, const void* _token) nogil:
cdef atom_t[N_CONTEXT_FIELDS] context
memset(context, 0, sizeof(context))
token = <const TokenC*>_token token = <const TokenC*>_token
_fill_from_token(&eg.atoms[P2_orth], token - 2) _fill_from_token(&context[P2_orth], token - 2)
_fill_from_token(&eg.atoms[P1_orth], token - 1) _fill_from_token(&context[P1_orth], token - 1)
_fill_from_token(&eg.atoms[W_orth], token) _fill_from_token(&context[W_orth], token)
_fill_from_token(&eg.atoms[N1_orth], token + 1) _fill_from_token(&context[N1_orth], token + 1)
_fill_from_token(&eg.atoms[N2_orth], token + 2) _fill_from_token(&context[N2_orth], token + 2)
eg.nr_feat = self.extracter.set_features(eg.features, eg.atoms) return self.extracter.set_features(features, context)
cdef inline void _fill_from_token(atom_t* context, const TokenC* t) nogil: cdef inline void _fill_from_token(atom_t* context, const TokenC* t) nogil:
@ -202,7 +204,7 @@ cdef class Tagger:
nr_feat=self.model.nr_feat) nr_feat=self.model.nr_feat)
for i in range(tokens.length): for i in range(tokens.length):
if tokens.c[i].pos == 0: if tokens.c[i].pos == 0:
self.model.set_featuresC(eg.c, &tokens.c[i]) eg.c.nr_feat = self.model.set_featuresC(eg.c.features, &tokens.c[i])
self.model.set_scoresC(eg.c.scores, self.model.set_scoresC(eg.c.scores,
eg.c.features, eg.c.nr_feat) eg.c.features, eg.c.nr_feat)
guess = VecVec.arg_max_if_true(eg.c.scores, eg.c.is_valid, eg.c.nr_class) guess = VecVec.arg_max_if_true(eg.c.scores, eg.c.is_valid, eg.c.nr_class)
@ -232,7 +234,7 @@ cdef class Tagger:
nr_class=self.vocab.morphology.n_tags, nr_class=self.vocab.morphology.n_tags,
nr_feat=self.model.nr_feat) nr_feat=self.model.nr_feat)
for i in range(tokens.length): for i in range(tokens.length):
self.model.set_featuresC(eg.c, &tokens.c[i]) eg.c.nr_feat = self.model.set_featuresC(eg.c.features, &tokens.c[i])
eg.costs = [ 1 if golds[i] not in (c, -1) else 0 for c in xrange(eg.nr_class) ] eg.costs = [ 1 if golds[i] not in (c, -1) else 0 for c in xrange(eg.nr_class) ]
self.model.set_scoresC(eg.c.scores, self.model.set_scoresC(eg.c.scores,
eg.c.features, eg.c.nr_feat) eg.c.features, eg.c.nr_feat)