This repository contains a Tensorflow implementation of Salesforce Research's Quasi-Recurrent Neural Networks paper. It supports batch-major or time-major inputs in single or double precision.
From the authors:
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:
pip3 install qrnn
If you use this code or their results in your research, you should 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}
}
The original PyTorch implementation of the QRNN can be found here.
- Tensorflow 1.4 (
pip install tensorflow
orpip install tensorflow-gpu
) - GCC
- CUDA (optional, needed for GPU support)
python3 test/test_fo_pool.py
- create wheels for Fedora, Ubuntu, etc...