def main():
lang_train_list = []
if len(sys.argv) == 1:
lang_train_list = ['swedish', 'danish', 'english']
else:
lang_train_list = sys.argv[1:]
random.seed(1126)
for lang in lang_train_list:
whole_data = get_train_data_from_lang(lang)
subdata = random.sample(whole_data, 200)
tp = TransitionParser(Transition, FeatureExtractor)
print '\n===== Start training {} data ====='.format(lang)
tp.train(subdata)
tp.save(lang + '.model')
print '===== Sucessfully generating models ====='
from providedcode import dataset
from providedcode.transitionparser import TransitionParser
from providedcode.evaluate import DependencyEvaluator
from featureextractor import FeatureExtractor
from transition import Transition
if __name__ == '__main__':
# traindata = dataset.get_swedish_train_corpus().parsed_sents()
traindata = dataset.get_english_train_corpus().parsed_sents()
try:
tp = TransitionParser(Transition, FeatureExtractor)
tp.train(traindata)
# tp.save('swedish.model')
# labeleddata = dataset.get_swedish_dev_corpus().parsed_sents()
# blinddata = dataset.get_swedish_dev_blind_corpus().parsed_sents()
tp.save('english.model')
labeleddata = dataset.get_english_dev_corpus().parsed_sents()
blinddata = dataset.get_english_dev_blind_corpus().parsed_sents()
#tp = TransitionParser.load('badfeatures.model')
# parsed = tp.parse(labeleddata)
parsed = tp.parse(blinddata)
with open('test.conll', 'w') as f:
for p in parsed:
f.write(p.to_conll(10).encode('utf-8'))
parsed = tp.parse(testdata)
with open('test.conll', 'w') as f:
for p in parsed:
f.write(p.to_conll(10).encode('utf-8'))
f.write('\n')
ev = DependencyEvaluator(testdata, parsed)
print "Bad Features Results"
print "UAS: {} \nLAS: {}".format(*ev.eval())
t1 = time.time()
print "Time: " + str(t1 - t0) + '\n'
# SWEDISH FEATURE MODELS
print 'Starting Swedish'
tp_s = TransitionParser(Transition, FeatureExtractor)
tp_s.train(subdata)
tp_s.save('swedish.model')
testdata = dataset.get_swedish_test_corpus().parsed_sents()
tp_s = TransitionParser.load('swedish.model')
parsed = tp_s.parse(testdata)
with open('swedish.conll', 'w') as f:
for p in parsed:
f.write(p.to_conll(10).encode('utf-8'))
f.write('\n')
ev = DependencyEvaluator(testdata, parsed)
print "Swedish Results"
