b74255e1f3c5d9344b68534a5549c354da7b031b
				
			
			
		
	Neural Architecture Search Without Training
⚠️ Note: this repository has been updated to reflect the second version of the paper to appear on arXiv 1 March. :warning
Usage
Create a conda environment using the env.yml file
conda env create -f env.yml
Activate the environment and follow the instructions to install
Install nasbench (see https://github.com/google-research/nasbench)
Download the NDS data from https://github.com/facebookresearch/nds and place the json files in naswot-codebase/nds_data/ 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)
Reproduce all of the results by running
./scorehook.sh
The code is licensed under the MIT licence.
Citing us
If you use or build on our work, please consider citing us:
@misc{mellor2020neural,
    title={Neural Architecture Search without Training},
    author={Joseph Mellor and Jack Turner and Amos Storkey and Elliot J. Crowley},
    year={2020},
    eprint={2006.04647},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}
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