the final output was created from the rest of the sequence we should be able to take the final output and pass it to the feed-forward layer to classify in intent for those of you who like looking at code here are some Python showcasing the control flow first you initialize your network layers in the initial hidden state the shape and dimensions of the hidden state will be dependent on the shape and dimension of your recurrent rail network then you loop through your inputs past a word and hence a into the artnet DRN and returns