def test_save_and_load_model(self):
pre_model = self.create_test_model()
pre_model.train(iter=10000)
p1 = pre_model.perplexity()
pre_model.save()
r = self.get_resource()
post_model = GTopicModel.load(r.path)
p2 = post_model.perplexity()
self.assertTrue((p1 - p2) < 1e-5)
# document (corpus)
p = PickleResource(path)
doc = p.load()
training, test = doc.split(right_rate_or_size=0.3, compact=False)
model = None
perplexity = 1e5
topics = [args.topics]
if args.till:
topics = range(args.topics, args.till + 1)
for t in topics:
print("topic count = {0}".format(t))
for e in range(args.epoch):
# make model
m = GTopicModel(t, training, resource=r)
m.train(iter=args.iter, burn=args.burn)
p = m.perplexity(test)
if p < perplexity:
model = m
perplexity = p
print("\t epoch{0}: perplexity = {1}".format(e, p))
print(
"model is created. topics={0}, perplexity is {1}/{2} (training/test)".format(
model.topic_count, model.perplexity(), model.perplexity(test))
)
model.save()