aw_nas: A Modularized and Extensible NAS framework

Xuefei Ning; Changcheng Tang; Wenshuo Li; Songyi Yang; Tianchen Zhao; Niansong Zhang; Tianyi Lu; Shuang Liang; Huazhong Yang; Yu Wang

arXiv · 2012.10388

aw_nas: A Modularized and Extensible NAS framework

Xuefei Ning·Changcheng Tang·Wenshuo Li·Songyi Yang·Tianchen Zhao·Niansong Zhang·Tianyi Lu·Shuang Liang·Huazhong Yang·Yu Wang

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Abstract

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.

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BibTeX RIS

Xuefei Ning, Changcheng Tang, Wenshuo Li, Songyi Yang, Tianchen Zhao, Niansong Zhang, Tianyi Lu, Shuang Liang, Huazhong Yang, Yu Wang. 2020-11-25. aw_nas: A Modularized and Extensible NAS framework. https://arxiv.org/abs/2012.10388

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