论文标题
AW_NA：一个模块化且可扩展的NAS框架
aw_nas: A Modularized and Extensible NAS framework
论文作者
论文摘要
神经体系结构搜索（NAS）由于能力以自动化的方式发现神经网络体系结构，因此受到了广泛的关注。 AW_NAS是一种以模块化方式实现各种NAS算法的开源Python框架。当前，AW_NA可用于复制各种类型的主流NAS算法的结果。同样，由于模块化设计，可以简单地尝试使用AWNA的各种应用（例如，分类，检测，文本建模，容忍度，对抗性鲁棒性，硬件效率等）来尝试不同的NAS算法。代码和文档可在https://github.com/walkerning/aw_nas上找到。
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.
