Solved by tom in post #2 
              
              
                Many interesting RNN architectures use things besides what can be done with the “vanilla” RNN/GRU/LSTM - the classic is when one timestep’s output has an impact on the next timestep’s input - one prominent example is attention. 
Once you have things like that, you cannot use the multi-timesteps anym…