Solved by Adamits in post #2 
              
              
                Because the encoder is bidirectional. This means that one RNN is trained in one direction across your inputs, and the other is trained in the opposite direction. In order to represent each timestep of your RNN as informed by both what comes before, and what comes after, we represent each state as th…