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* Tmp commit of train, while I move to better alignment in gold standard

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This commit is contained in:
Matthew Honnibal 2015-05-23 17:21:25 +02:00
parent bdaddc4103
commit f35503018e
1 changed files with 26 additions and 16 deletions
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42
bin/parser/train.py
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@ -11,6 +11,7 @@ import random
import plac import plac
import cProfile import cProfile
import pstats import pstats
import re
import spacy.util import spacy.util
from spacy.en import English from spacy.en import English
@ -51,11 +52,10 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic', seed=0
gold_tuples = gold_tuples[:n_sents] gold_tuples = gold_tuples[:n_sents]
nlp = Language(data_dir=model_dir) nlp = Language(data_dir=model_dir)
print "Itn.\tUAS\tNER F.\tTag %" print "Itn.\tUAS\tNER F.\tTag %\tToken %"
for itn in range(n_iter): for itn in range(n_iter):
scorer = Scorer() scorer = Scorer()
for raw_text, segmented_text, annot_tuples, ctnt in gold_tuples: for raw_text, segmented_text, annot_tuples, ctnt in gold_tuples:
# Eval before train
tokens = nlp(raw_text, merge_mwes=False) tokens = nlp(raw_text, merge_mwes=False)
gold = GoldParse(tokens, annot_tuples) gold = GoldParse(tokens, annot_tuples)
scorer.score(tokens, gold, verbose=False) scorer.score(tokens, gold, verbose=False)
@ -67,12 +67,18 @@ def train(Language, gold_tuples, 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) try:
nlp.parser.train(tokens, gold)
except AssertionError:
# TODO: Do something about non-projective sentences
continue
if gold.ents: if gold.ents:
nlp.entity.train(tokens, 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\t%.3f' % (itn, scorer.uas, scorer.ents_f,
scorer.tags_acc,
scorer.token_acc)
random.shuffle(gold_tuples) random.shuffle(gold_tuples)
nlp.parser.model.end_training() nlp.parser.model.end_training()
nlp.entity.model.end_training() nlp.entity.model.end_training()
@ -106,18 +112,22 @@ def write_parses(Language, dev_loc, model_dir, out_loc):
def get_sents(json_dir, section): def get_sents(json_dir, section):
if section == 'train': if path.exists(path.join(json_dir, section + '.json')):
file_range = range(2, 22) for sent in read_json_file(path.join(json_dir, section + '.json')):
elif section == 'dev':
file_range = range(22, 23)
for i in file_range:
sec = str(i)
if len(sec) == 1:
sec = '0' + sec
loc = path.join(json_dir, sec + '.json')
for sent in read_json_file(loc):
yield sent yield sent
else:
if section == 'train':
file_range = range(2, 22)
elif section == 'dev':
file_range = range(22, 23)
for i in file_range:
sec = str(i)
if len(sec) == 1:
sec = '0' + sec
loc = path.join(json_dir, sec + '.json')
for sent in read_json_file(loc):
yield sent
@plac.annotations( @plac.annotations(
@ -137,7 +147,7 @@ def main(json_dir, model_dir, n_sents=0, out_loc="", verbose=False,
write_parses(English, dev_loc, model_dir, out_loc) write_parses(English, dev_loc, model_dir, out_loc)
scorer = evaluate(English, list(get_sents(json_dir, 'dev')), scorer = evaluate(English, list(get_sents(json_dir, 'dev')),
model_dir, gold_preproc=False, verbose=verbose) model_dir, gold_preproc=False, verbose=verbose)
print 'TOK', scorer.mistokened print 'TOK', 100-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