def test_kldiv(self):
p = np.array([[0.1, 0.4, 0.3, 0.9]])
q1 = np.array([[0.1, 0.2, 0.2, 0.5]])
q2 = np.array([[0.1, 0.4, 0.3, 0.8]])
self.assertTrue(TopicModel.kldiv(p, p) == 0)
d1 = TopicModel.kldiv(p, q1)
self.assertGreater(d1, 0)
d2 = TopicModel.kldiv(p, q2)
self.assertGreater(d1, d2)
def test_save_and_load_model(self):
batch_size = 100
pre_model = self.create_test_model()
pre_model.train(iter=batch_size, burn=0)
self.assertTrue(len(pre_model.core.trace("z_0")[:]) == batch_size)
pre_z = [z.value for z in pre_model.variables["z"]]
p1 = pre_model.perplexity()
pre_model.save()
r = self.get_resource()
post_model = TopicModel.load(r.path)
post_z = [z.value for z in post_model.variables["z"]]
for i, z in enumerate(post_z):
self.assertEqual(0, sum(z != pre_z[i]))
p2 = post_model.perplexity()
post_model.train(iter=batch_size, burn=0)
self.assertTrue(len(post_model.core.trace("z_0", chain=None)[:]) == (2 * batch_size))
self.assertEqual(p1, p2)
