def test_seq_scoring(self):
vocsize = 100
dim = 10
numsam = 17
seqlen = 5
ve = VectorEmbed(vocsize, dim)
m = SeqMatchScore(SeqUnroll(ve), SeqUnroll(ve), scorer=CosineDistance())
data = np.random.randint(0, vocsize, (numsam, seqlen))
#print data.shape
pred = m.predict(data, data)
#print pred
self.assertTrue(np.allclose(np.ones_like(pred)*seqlen*1., pred))
