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change the candidate's input resolution

See original GitHub issue

Hi, I would like to use you NATS-Bench for other datasets except cifar and Imagenet, and with higher resolutions like (256*256). Is it possible to sample a network like what you did for cifar below and then change the cells resolutions?

import xautodl, nats_bench

from nats_bench import create
from xautodl.models import get_cell_based_tiny_net

api = create(None, 'tss', fast_mode=True, verbose=True)

config = api.get_net_config(12, 'cifar10')
network = get_cell_based_tiny_net(config)

#then a code to change the input resolution to the target size of 256*256

Thanks for your response

Issue Analytics

  • State:closed
  • Created 2 years ago
  • Comments:5 (3 by maintainers)

github_iconTop GitHub Comments

D-X-Ycommented, Aug 7, 2021

Yes, you are right.

BTW, if you want to resize the CIFAR-10 size, you need to add a “resize transform” at here and also revised the shape at here, which is used to compute the FLOPs.

D-X-Ycommented, Oct 12, 2021

To increase the number of downsample layers, you need to change the definition of TinyNetwork. Please see here:, a True means a downsample layer.

Read more comments on GitHub >

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