Python 通过其他文件导入时，Gensim models.LdaMulticore（）不执行

代码发现test.py运行正常。但是在test2.py文件中导入test.py时，创建LDA多核模型的行似乎被卡住了

我添加了示例代码来说明这个问题。有解决办法吗

test.py：

from sklearn.feature_extraction.text import CountVectorizer
from gensim import corpora, models
from gensim.matutils import Sparse2Corpus
import time

data_clean = ["This is the first example document.","This is the second example document.","This is the third and last exaple document"]

vectorizer = CountVectorizer(analyzer='word', ngram_range=(1,1), min_df = 0.0001, max_df=0.8,stop_words = 'english')
matrix =  vectorizer.fit_transform(data_clean)

id2words = dict()
for k, v in vectorizer.vocabulary_.iteritems():
    id2words[v] = k

train_corpus = Sparse2Corpus(matrix, documents_columns=False)

if __name__ == 'test':
    print "The file is being imported"
    model = models.LdaMulticore(train_corpus ,id2word=id2words,num_topics=10, workers=4)
else:
    print "The file is directly executed"
    model = models.LdaMulticore(train_corpus ,id2word=id2words,num_topics=10, workers=4)

test2.py：

import test

终端输出：