python: using gensim.models.LdaSeqModel to configure a model but it can not be saved

I used 137874 documents to configure a dynamic model by gensim.models.LdaSeqModel with 76 time slots, but when debugging finished, the model was not saved. The program did not report any errors during the running process. I tried to test my code with a small data set and trained the model and it can be saved. What is the problem and how can I solve it?

from gensim.models import LdaSeqModel
of gensim import corpus

bow_corpus = corpora.MmCorpus (& # 39; / home / user / data / matrix.mm & # 39;)

dictionary = corpora.Dictionary.load (& # 39; / home / user / data / dic.dic & # 39;)

time_slice = [1, 1, 6, 101, 41, 26, 23, 18, 22, 26, 30, 45, 59, 94, 87, 110, 121,
              128, 106, 144, 172, 155, 181, 172, 166, 192, 275, 330, 374, 358, 411, 585,
              583, 508, 534, 671, 625, 860, 650, 612, 804, 842, 803, 733, 783, 1277, 1528,
              1583, 1685, 1696, 2091, 2502, 2433, 2830, 2860, 3067, 3545, 3241, 3663, 3653,
              3513, 3799, 3753, 4198, 4394, 4661, 4833, 4983, 6386, 4874, 6739, 6969, 7207,
              7244, 7291, 5808]

dtm = LdaSeqModel (corpus = bow_corpus, time_slice = time_slice, id2word = dictionary, num_topics = 77, passes = 1)

dtm.save (& # 39; / home / user / data / dtm.model & # 39;)