Now that we have learned how an RNN works, we will look at a different type of RNN architecture that's based on numbers of input and output.
Different types of RNN architectures
One-to-one architecture
In a one-to-one architecture, a single input is mapped to a single output, and the output from the time step t is fed as an input to the next time step. We have already seen this architecture in the last section for generating songs using RNNs.
For instance, for a text generation task, we take the output generated from a current time step and feed it as the input to the next time step to generate the next word. This architecture is also widely used in stock market predictions.
The following figure shows the one-to-one RNN...