def train_test(self, model_type, compare=True):
passages = [self.passage]
scores = []
for mode in "train", "load":
print("-- %sing %s" % (mode, model_type))
p = Parser(model_file="test_files/%s" % model_type, model_type=model_type)
p.train(passages if mode == "train" else None)
guess, ref = zip(*list(p.parse(passages)))
print()
self.assertSequenceEqual(ref, passages)
score = evaluation.Scores.aggregate([evaluation.evaluate(
g, r, verbose=False, units=False, errors=False)
for g, r in zip(guess, ref)])
scores.append(score.average_f1())
if compare:
self.assertEqual(*scores)
print("-- average labeled f1: %.3f, %.3f" % tuple(scores))
def train_test(passages, *args, **kwargs):
p = Parser(*args, **kwargs)
p.train(passages)
_, parsed = zip(*p.parse(passages))
return parsed
def train_test(passages, *args, **kwargs):
p = Parser(*args, **kwargs)
p.train(passages)
_, parsed = zip(*p.parse(passages))
return parsed
