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Fix tagger training

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This commit is contained in:
Matthew Honnibal 2017-09-23 02:58:06 +02:00
parent a2357cce3f
commit 386c1a5bd8
1 changed files with 4 additions and 5 deletions
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9
spacy/pipeline.pyx
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@ -343,6 +343,7 @@ class NeuralTagger(BaseThincComponent):
tag_scores, bp_tag_scores = self.model.begin_update(docs, drop=drop)
loss, d_tag_scores = self.get_loss(docs, golds, tag_scores)
bp_tag_scores(d_tag_scores, sgd=sgd)
if losses is not None:
losses[self.name] += loss
@ -386,15 +387,13 @@ class NeuralTagger(BaseThincComponent):
vocab.morphology = Morphology(vocab.strings, new_tag_map,
vocab.morphology.lemmatizer,
exc=vocab.morphology.exc)
token_vector_width = pipeline[0].model.nO
if self.model is True:
self.model = self.Model(self.vocab.morphology.n_tags, token_vector_width,
self.model = self.Model(self.vocab.morphology.n_tags,
pretrained_dims=self.vocab.vectors_length)
@classmethod
def Model(cls, n_tags, token_vector_width, pretrained_dims=0, **cfg):
return build_tagger_model(n_tags, token_vector_width,
pretrained_dims, **cfg)
def Model(cls, n_tags, **cfg):
return build_tagger_model(n_tags, **cfg)
def use_params(self, params):
with self.model.use_params(params):