Just as we can increase the depth of neural networks or CNNs, we can increase the depth of RNN networks. In this recipe we apply a three-layer-deep LSTM to improve our Shakespearean language generation.
Stacking multiple LSTM layers
Getting ready
We can increase the depth of recurrent neural networks by stacking them on top of each other. Essentially, we will be taking the target outputs and feeding them into another network.
To get an idea of how this might work for just two layers, see the following diagram:
Figure 5: In the preceding diagram, we have extended one-layer RNNs so that they have two layers. For the original one-layer versions, see the diagrams in the introduction to the previous chapter. The left architecture...
