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spaCy
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* Use print function in train.py, for py 2/3 compatibility

This commit is contained in:
Matthew Honnibal 2015-07-24 04:52:35 +02:00
parent d62eb34b76
commit c52179f5fa
1 changed files with 11 additions and 10 deletions
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21
bin/parser/train.py
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@ -1,6 +1,7 @@
#!/usr/bin/env python #!/usr/bin/env python
from __future__ import division from __future__ import division
from __future__ import unicode_literals from __future__ import unicode_literals
from __future__ import print_function
import os import os
from os import path from os import path
@ -107,7 +108,7 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic',
nlp = Language(data_dir=model_dir) nlp = Language(data_dir=model_dir)
print "Itn.\tP.Loss\tUAS\tNER F.\tTag %\tToken %" print("Itn.\tP.Loss\tUAS\tNER F.\tTag %\tToken %")
for itn in range(n_iter): for itn in range(n_iter):
scorer = Scorer() scorer = Scorer()
loss = 0 loss = 0
@ -138,9 +139,9 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic',
nlp.entity.train(tokens, gold) nlp.entity.train(tokens, gold)
nlp.tagger.train(tokens, gold.tags) nlp.tagger.train(tokens, gold.tags)
random.shuffle(gold_tuples) random.shuffle(gold_tuples)
print '%d:\t%d\t%.3f\t%.3f\t%.3f\t%.3f' % (itn, loss, scorer.uas, scorer.ents_f, print('%d:\t%d\t%.3f\t%.3f\t%.3f\t%.3f' % (itn, loss, scorer.uas, scorer.ents_f,
scorer.tags_acc, scorer.tags_acc,
scorer.token_acc) scorer.token_acc))
nlp.end_training() nlp.end_training()
def evaluate(Language, gold_tuples, model_dir, gold_preproc=False, verbose=False, def evaluate(Language, gold_tuples, model_dir, gold_preproc=False, verbose=False,
@ -219,14 +220,14 @@ def main(train_loc, dev_loc, model_dir, n_sents=0, n_iter=15, out_loc="", verbos
# write_parses(English, dev_loc, model_dir, out_loc, beam_width=beam_width) # write_parses(English, dev_loc, model_dir, out_loc, beam_width=beam_width)
scorer = evaluate(English, list(read_json_file(dev_loc)), scorer = evaluate(English, list(read_json_file(dev_loc)),
model_dir, gold_preproc=gold_preproc, verbose=verbose) model_dir, gold_preproc=gold_preproc, verbose=verbose)
print 'TOK', scorer.token_acc print('TOK', scorer.token_acc)
print 'POS', scorer.tags_acc print('POS', scorer.tags_acc)
print 'UAS', scorer.uas print('UAS', scorer.uas)
print 'LAS', scorer.las print('LAS', scorer.las)
print 'NER P', scorer.ents_p print('NER P', scorer.ents_p)
print 'NER R', scorer.ents_r print('NER R', scorer.ents_r)
print 'NER F', scorer.ents_f print('NER F', scorer.ents_f)
if __name__ == '__main__': if __name__ == '__main__':