The recurrent computation library contains code to perform recurrent computations.
Its chief application is to implement recurrent neural networks (RNNs, LSTMs, etc), which is implemented in functional_rnn.py. Similar techniques may be used to implement deep networks.
The computation saves the activations in the forward pass, and computes the gradients in the backward pass using a single accumulator.
The functional_rnn interface is compatible with the dynamic_rnn API.