change the candidate's input resolution

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

[D-X-Y]

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-Y]

To increase the number of downsample layers, you need to change the definition of TinyNetwork. Please see here: https://github.com/D-X-Y/AutoDL-Projects/blob/58733c18becf18cd5c66392eb0ca6a80e2d14d23/xautodl/models/cell_infers/tiny_network.py#L21, a True means a downsample layer.