def __init__(self):
self.s2v = sentence2vec.Sentence2Vec()
self.model_set = []
# Read neural network model from file.
file_list = listdir(''.join([dirname(abspath(__file__)), '/model']))
file_list.sort()
for f in file_list:
self.model_set.append(builder.ModelBuilder(f))
def __init__(self):
self.s2v = sentence2vec.Sentence2Vec() # 예시 문장들 파싱할 Sentence2Vec 객체 생성
from os.path import abspath
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
sys.path.insert(0, abspath('../sentence2vec'))
import numpy as np
import modelbuilder as mb
import sentence2vec
if __name__ == '__main__':
if len(sys.argv) < 3:
print '$python test.py model_number sentence_to_test'
exit()
model = mb.ModelBuilder(sys.argv[1])
s2v = sentence2vec.Sentence2Vec()
result = np.array(s2v.sentence2vec(sys.argv[2]))
status_1 = np.zeros([100])
status_2 = np.zeros([100])
for i in xrange(result.shape[0]):
output, status_1, status_2 = model.run(result[i, :], status_1,
status_2)
print 'prob :', output