NAS-Bench-201 contains a lot of information and is therefore very big.
In my experience I rarely need access to all of the information to run an experiment, just a small subset (e.g. just the model accuracies)
This is a simple way to generate a small file which contains only the information you need. Either you can use the minibench file provided directly or you can generate your own with the info you want.
On my machine, loading minibench took 0.0062 seconds, where NAS-Bench-201 took 61.0529 seconds.
First, copy the minibench-arch-cell-accs.pd file into your repository.
import pandas as pd
minibench = pd.read_pickle('minibench-arch-cell-accs.pd')
## get accuracy for arch 42 on cifar10-val
cifar10_val = minibench.iloc[42]['cifar10-val']You can also iloc with a list of indices. The rows correspond to the NAS-Bench-201 architecture IDs.
The default column names are:
columns=['arch','cellstr','cifar10-test','cifar10-val', 'cifar100-test', 'cifar100-val', 'imagenet-test', 'imagenet-val']