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* Remove support for force_gold flag from GreedyParser, since it's not so useful, and it's clutter

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This commit is contained in:
Matthew Honnibal 2015-03-24 05:12:37 +01:00
parent 6a6085f8b9
commit e854ba0a13
2 changed files with 9 additions and 10 deletions
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8
bin/parser/train.py
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@ -187,7 +187,7 @@ def get_labels(sents):
def train(Language, train_loc, model_dir, n_iter=15, feat_set=u'basic', seed=0, def train(Language, train_loc, model_dir, n_iter=15, feat_set=u'basic', seed=0,
gold_preproc=False, force_gold=False, n_sents=0): gold_preproc=False, n_sents=0):
dep_model_dir = path.join(model_dir, 'deps') dep_model_dir = path.join(model_dir, 'deps')
pos_model_dir = path.join(model_dir, 'pos') pos_model_dir = path.join(model_dir, 'pos')
ner_model_dir = path.join(model_dir, 'ner') ner_model_dir = path.join(model_dir, 'ner')
@ -230,8 +230,8 @@ def train(Language, train_loc, model_dir, n_iter=15, feat_set=u'basic', seed=0,
for tokens in sents: for tokens in sents:
gold = GoldParse(tokens, annot_tuples) gold = GoldParse(tokens, annot_tuples)
nlp.tagger(tokens) nlp.tagger(tokens)
nlp.parser.train(tokens, gold, force_gold=force_gold) nlp.parser.train(tokens, gold)
nlp.entity.train(tokens, gold, force_gold=force_gold) nlp.entity.train(tokens, gold)
nlp.tagger.train(tokens, gold.tags) nlp.tagger.train(tokens, gold.tags)
print '%d:\t%.3f\t%.3f\t%.3f' % (itn, scorer.uas, scorer.ents_f, scorer.tags_acc) print '%d:\t%.3f\t%.3f\t%.3f' % (itn, scorer.uas, scorer.ents_f, scorer.tags_acc)
@ -280,7 +280,7 @@ def write_parses(Language, dev_loc, model_dir, out_loc):
def main(train_loc, dev_loc, model_dir, n_sents=0, out_loc="", verbose=False, def main(train_loc, dev_loc, model_dir, n_sents=0, out_loc="", verbose=False,
debug=False): debug=False):
train(English, train_loc, model_dir, feat_set='basic' if not debug else 'debug', train(English, train_loc, model_dir, feat_set='basic' if not debug else 'debug',
gold_preproc=False, force_gold=False, n_sents=n_sents) gold_preproc=False, n_sents=n_sents)
if out_loc: if out_loc:
write_parses(English, dev_loc, model_dir, out_loc) write_parses(English, dev_loc, model_dir, out_loc)
scorer = evaluate(English, dev_loc, model_dir, gold_preproc=False, verbose=verbose) scorer = evaluate(English, dev_loc, model_dir, gold_preproc=False, verbose=verbose)

11
spacy/syntax/parser.pyx
View File

@ -93,7 +93,7 @@ cdef class GreedyParser:
tokens.set_parse(state.sent) tokens.set_parse(state.sent)
return 0 return 0
def train(self, Tokens tokens, GoldParse gold, force_gold=False): def train(self, Tokens tokens, GoldParse gold):
self.moves.preprocess_gold(gold) self.moves.preprocess_gold(gold)
cdef Pool mem = Pool() cdef Pool mem = Pool()
cdef State* state = new_state(mem, tokens.data, tokens.length) cdef State* state = new_state(mem, tokens.data, tokens.length)
@ -109,12 +109,11 @@ cdef class GreedyParser:
while not is_final(state): while not is_final(state):
fill_context(context, state) fill_context(context, state)
scores = self.model.score(context) scores = self.model.score(context)
guess = self.moves.best_valid(scores, state) guess = self.moves.best_valid(scores, state)
best = self.moves.best_gold(scores, state, gold) best = self.moves.best_gold(scores, state, gold)
cost = guess.get_cost(&guess, state, gold) cost = guess.get_cost(&guess, state, gold)
self.model.update(context, guess.clas, best.clas, cost) self.model.update(context, guess.clas, best.clas, cost)
if force_gold:
best.do(&best, state) guess.do(&guess, state)
else:
guess.do(&guess, state)