Neural Architecture Search (NAS) has received extensive attention due to its capability to discover neural network architectures in an automated manner. aw_nas is an open-source Python framework implementing various NAS algorithms in a modularized manner. Currently, aw_nas can be used to reproduce the results of mainstream NAS algorithms of various types. Also, due to the modularized design, one can simply experiment with different NAS algorithms for various applications with awnas (e.g., classification, detection, text modeling, fault tolerance, adversarial robustness, hardware efficiency, and etc.). Codes and documentation are available at https://github.com/walkerning/aw_nas.
@article{arxiv.2012.10388,
title = {aw_nas: A Modularized and Extensible NAS framework},
author = {Xuefei Ning and Changcheng Tang and Wenshuo Li and Songyi Yang and Tianchen Zhao and Niansong Zhang and Tianyi Lu and Shuang Liang and Huazhong Yang and Yu Wang},
journal= {arXiv preprint arXiv:2012.10388},
year = {2020}
}