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Quasi-Recurrent Neural Network (QRNN) :准循环神经网络 PyTorch 实现

准循环神经网络 QRNN 提供了和 LSTM 相似的精度,但是可以 2 到 17 倍快比高度优化的 NVIDIA cuDNN LSTM 实现基于使用实例。

Quasi-Recurrent Neural Network (QRNN) for PyTorch

项目地址:https://github.com/salesforce/pytorch-qrnn

这个项目包含一个 PyTorch 实现的 Salesforce Research’s Quasi-Recurrent Neural Networks 论文.

This repository contains a PyTorch implementation of Salesforce Research’s Quasi-Recurrent Neural Networks paper.

The QRNN provides similar accuracy to the LSTM but can be betwen 2 and 17 times faster than the highly optimized NVIDIA cuDNN LSTM implementation depending on the use case.

To install, simply run:

pip install cupy pynvrtc git+https://github.com/salesforce/pytorch-qrnn

If you use this code or our results in your research, please cite:

@article{bradbury2016quasi,
title={{Quasi-Recurrent Neural Networks}},
author={Bradbury, James and Merity, Stephen and Xiong, Caiming and Socher, Richard},
journal={International Conference on Learning Representations (ICLR 2017)},
year={2017}
}

原创文章,作者:fendouai,如若转载,请注明出处:https://panchuang.net/2017/10/11/quasi-recurrent-neural-network-qrnn-for-pytorch/

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