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This repository is pytorch version implement of LRU from the paper "Resurrecting Recurrent Neural Networks for Long Sequences" (https://arxiv.org/abs/2303.06349), which is based on tf version by @bojon

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lru_pytorch's Introduction

PyTorch implementation of LRU (Linear Recurrent Unit)

This Repository implements a pytorch version of the LRU, including parallel training and serial inference.

The parallel acceleration is achieved by Upper/Lower algorithm based on Bojbojone/rnn.

About LRU

LRU is proposed by Resurrecting Recurrent Neural Networks for Long Sequences as an alternative to RNNs, with an architecture inspired by SSMs. I conducted experiments on a classification problem in finance, and the results showed a significant improvement of LRU over LSTM.

Notes

If you want to use LRU for time series prediction, please note that the paper requires LRU with MLP for this, while merely LRU is implemented in this project.

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