The architecture for Cifar-100 dataset about mixmatch

[david-berthelot]

See how to reproduce tables in runs folder:
https://github.com/google-research/mixmatch/blob/master/runs/table1.sh

Basically we pass the option --filters=135 (instead of 32), as you can see in libml/models.py the layers grow proportionally to that number in the resnet architecture (and in other architectures too).

[wang3702]

That's to say, it starts from 135, then 270, then 405 and 540(for 4 blocks). If my understanding is correctly, I will close the issue. Thanks!

[wang3702]

Sorry for my incorrect calculation. Here the number of filters should from 135,270,540,1080. Is that Correct?

[wang3702]

I have checked that: that's around Total params: 104.6074160000M. In your paper, it's around 26 million parameter. Could you please explain more detailed?

[wang3702]

I figured out:
it's 16, 135,270,540.
Total number of params: 26.1161800000M
Is my understanding correct?

[david-berthelot]

I don't recall the exact number, in the paper we quoted 26M. When you run the code you can see the size of the network parameters layer by layer before training start.