if __name__ == "__main__":
WORD_VOCAB_FILE = 'data/words.vocab'
POS_VOCAB_FILE = 'data/pos.vocab'
try:
word_vocab_f = open(WORD_VOCAB_FILE,'r')
pos_vocab_f = open(POS_VOCAB_FILE,'r')
except FileNotFoundError:
print("Could not find vocabulary files {} and {}".format(WORD_VOCAB_FILE, POS_VOCAB_FILE))
sys.exit(1)
extractor = FeatureExtractor(word_vocab_f, pos_vocab_f)
parser = Parser(extractor, sys.argv[1])
total_labeled_correct = 0
total_unlabeled_correct = 0
total_words = 0
las_list = []
uas_list = []
count = 0
with open(sys.argv[2],'r') as in_file:
print("Evaluating. (Each . represents 100 test dependency trees)")
for dtree in conll_reader(in_file):
words = dtree.words()
pos = dtree.pos()
predict = parser.parse_sentence(words, pos)
if __name__ == "__main__":
WORD_VOCAB_FILE = 'data/words.vocab'
POS_VOCAB_FILE = 'data/pos.vocab'
try:
word_vocab_f = open(WORD_VOCAB_FILE, 'r')
pos_vocab_f = open(POS_VOCAB_FILE, 'r')
except FileNotFoundError:
print("Could not find vocabulary files {} and {}".format(
WORD_VOCAB_FILE, POS_VOCAB_FILE))
sys.exit(1)
extractor = FeatureExtractor(word_vocab_f, pos_vocab_f)
parser = Parser(extractor, 'data/model.h5')
total_labeled_correct = 0
total_unlabeled_correct = 0
total_words = 0
las_list = []
uas_list = []
count = 0
with open('data/dev.conll', 'r') as in_file:
print("Evaluating. (Each . represents 100 test dependency trees)")
for dtree in conll_reader(in_file):
words = dtree.words()
pos = dtree.pos()
predict = parser.parse_sentence(words, pos)