This repo is the implementation of Revisiting Training-free NAS Metrics: An Efficient Training-based Method at WACV 2023.
If you find our work useful in your research, please consider citing us:
@inproceedings{yang2023revisiting,
title={Revisiting Training-free NAS Metrics: An Efficient Training-based Method},
author={Yang, Taojiannan and Yang, Linjie and Jin, Xiaojie and Chen, Chen},
booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={4751--4760},
year={2023}
}
python = 3.8.12, pytorch = 1.7.1
Install NASBench following instructions in https://github.com/google-research/nasbench
Download the NASbench101 data (see https://github.com/google-research/nasbench)
Download the NASbench201 data (see https://github.com/D-X-Y/NAS-Bench-201)
To run the experiments, use the script:
bash run_exp.sh
The code is based on the implementation of NASWOT