Our model uses a second RNN encoder to represent the output as another fixed length vector.
our model is During training we use maximum likelihood to estimate θ given a large set of valid input-output pairs where each y i belongs to Y which in general is much larger than W. Our main challenge during training is that Y is intractably large for computing Z.