def __init__(self, filename):
self.Y = Alphabet()
data = list(
fromSGML(filename, linegrouper="<NEW.*?>", bioencoding=False))
np.random.shuffle(data)
super(CoraCitations, self).__init__(train=data[len(data) // 5:],
dev=data[:len(data) // 5],
test=[])
self.train = self.make_instances('train', Instance)
self.dev = self.make_instances('dev', Instance)
def get_data(f):
for x in fromSGML(f, linegrouper="<NEW.*?>", bioencoding=False):
x, y = zip(*[(Token(w), y) for y, w in x])
preprocessing(x)
yield Instance(x, truth=y)