Understanding Bidirectional RNN in PyTorch – Towards Data Science

Bidirectional recursive neural networks(RNN) are really just putting two independent RNNs together. The input sequence is fed in normal time order for one network, and in reverse time order for another. The outputs of the two networks are usually concatenated at each time step, though there are other options, e.g. This structure allows the networks to have both backward and forward information about the sequence at every time step. The concept seems easy enough.