feyzaakyurek / subspace-reg Goto Github PK
View Code? Open in Web Editor NEWCode for the ICLR2022 paper on Subspace Regularization for few-shot class incremental image classification
License: MIT License
Code for the ICLR2022 paper on Subspace Regularization for few-shot class incremental image classification
License: MIT License
Hi, thanks for your inspiring work and detailed doc.
def get_projected_weight(self, pull, base_weight, weights):
tr = torch.transpose(base_weight, 0, 1)
Q, R = torch.qr(tr, some=True) # Q is 640x60
mut = weights @ Q # mut is 5 x 60
mutnorm = mut / torch.norm(base_weight, dim=1).unsqueeze(0)
return mutnorm @ base_weight
I wonder if there is a mistake when getting the projection vector 'm'. In my opinion, 'mut' is the coordinate of the orthogonal basis and the projection should be derived from mut @ Q
instead of mut @ base_weight
. Please let me know if I were wrong.
Thanks a lot!
Hi,
Thanks for this great study. I would like to reproduce you experimental results but I am not sure which file to run to get the experimental results. I followed the instructions from the README file for downloading and extracting files. I ran the train_supervised.py
file but got the following error:
FileNotFoundError: [Errno 2] No such file or directory: './data/miniImageNet\miniImageNet_category_split_train_phase_train.pickle'
It would be amazing if you could share how to use your code for reproducing the experiment results or using it for another datasets.
Thank you so much!
Hi, thanks for your inspiring work and detailed doc.
When I ran the sample scripts following your guide, I found that the value of SLURM_ARRAY_TASK_ID
is unknown. As a result, no log files were output. So I commented out the whole line if [[ $cnt -eq $SLURM_ARRAY_TASK_ID ]]; then
and gave a random value to SLURM_ARRAY_TASK_ID
, then everything seemed to be work properly.
I wonder whether the value of SLURM_ARRAY_TASK_ID
and the determine statement in sample scripts is necessary or not. Please let me know if I miss anything important.
Thanks a lot!
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