def METHOD_NAME(self):
    """Test using a SeqToSeq model as a variational autoenconder."""
    sequence_length = 10
    tokens = list(range(10))
    s = dc.models.SeqToSeq(tokens,
                           tokens,
                           sequence_length,
                           encoder_layers=2,
                           decoder_layers=2,
                           embedding_dimension=128,
                           learning_rate=0.01,
                           variational=True)
    # Actually training a VAE takes far too long for a unit test.  Just run a
    # few steps of training to make sure nothing crashes, then check that the
    # results are at least internally consistent.
    s.fit_sequences(generate_sequences(sequence_length, 1000))
    for sequence, target in generate_sequences(sequence_length, 10):
        pred1 = s.predict_from_sequences([sequence], beam_width=1)
        embedding = s.predict_embeddings([sequence])
        assert pred1 == s.predict_from_embeddings(embedding, beam_width=1)