Open ph-code-repo opened 5 months ago
Yes, I'd be happy to train that for you. I can create a d8resnet
using a base_width=20
which comes out to around the same number of trainable parameters as the other models. Here are some stats for it:
Num Params: 11.9M Eval forward pass (batchsize=1): 25ms | 3.4 Gb Train forward pass (batchsize=32): 230ms | 8.4 Gb
I got these numbers with an RTX2080Ti. Does this sound like it would work for your situation? It will take a few days to train so I want to confirm it's right for your application.
That is great news, thank you! Just to check, is the base_width
parameter the number of channels/kernels used in the first layer of ResNet, so that the number in the final layer of ResNet 18 would be 8 times this amount? In which case, I think this should be fine.
Thank you for responding so quickly!
It's training now, sorry for the delay. I'll upload the checkpoint by the end of the week.
Hi there, Would it be possible for you to train a d8 ResNet18 network for me. I'd really like to be able to have the same number of rotations as the C8 network, but within the dihedral group. I doubt that I have the resources to be able to train it myself.
Kind Regards!