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Insert into vocab, and print nr_weight and nr_feat

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This commit is contained in:
Matthew Honnibal 2016-09-01 10:45:06 +02:00
parent b73295557c
commit ed23476c82
1 changed files with 14 additions and 4 deletions
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18
bin/parser/conll_train.py
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@ -152,6 +152,11 @@ def train(Language, gold_tuples, model_dir, dev_loc, n_iter=15, feat_set=u'basic
rho=regularization)
nlp = Language(data_dir=model_dir, tagger=False, parser=False, entity=False)
# Insert into vocab
for _, sents in gold_tuples:
for annot_tuples, _ in sents:
for word in annot_tuples[1]:
_ = nlp.vocab[word]
nlp.tagger = Tagger.blank(nlp.vocab, Tagger.default_templates())
#nlp.parser = BeamParser.from_dir(dep_model_dir, nlp.vocab.strings, ArcEager)
nlp.parser = Parser.from_dir(dep_model_dir, nlp.vocab.strings, ArcEager)
@ -160,7 +165,7 @@ def train(Language, gold_tuples, model_dir, dev_loc, n_iter=15, feat_set=u'basic
print(nlp.parser.model.widths)
print("Itn.\tP.Loss\tTrain\tDev\tnr_weight")
print("Itn.\tP.Loss\tTrain\tDev\tnr_weight\tnr_feat")
last_score = 0.0
nr_trimmed = 0
eg_seen = 0
@ -177,6 +182,7 @@ def train(Language, gold_tuples, model_dir, dev_loc, n_iter=15, feat_set=u'basic
print("Dev before average", dev_uas)
nlp.parser.model.end_training()
nlp.parser.model.dump(path.join(model_dir, 'deps', 'model'))
print("Saved. Evaluating...")
return nlp
@ -198,10 +204,12 @@ def _train_epoch(nlp, gold_tuples, eg_seen, itn, dev_loc, micro_eval):
else:
dev_uas = 0.0
train_uas = score_sents(nlp, micro_eval).uas
size = nlp.parser.model.nr_weight
nr_upd = nlp.parser.model.time
print('%d,%d:\t%d\t%.3f\t%.3f\t%d' % (itn, nr_upd, int(loss),
train_uas, dev_uas, size))
nr_weight = nlp.parser.model.nr_weight
nr_feat = nlp.parser.model.nr_active_feat
print('%d,%d:\t%d\t%.3f\t%.3f\t%d\t%d' % (itn, nr_upd, int(loss),
train_uas, dev_uas,
nr_weight, nr_feat))
loss = 0
return eg_seen
@ -242,6 +250,8 @@ def main(train_loc, dev_loc, model_dir, n_iter=15, neural=False, batch_norm=Fals
print('POS', scorer.tags_acc)
print('UAS', scorer.uas)
print('LAS', scorer.las)
print('nr_weight', nlp.parser.model.nr_weight)
print('nr_feat', nlp.parser.model.nr_active_feat)
if __name__ == '__main__':