Adding swin to the self-supervised swav about lightning-bolts HOT 2 OPEN

SWAV is already implemented in lightning bolts. You will have to inherent SWAV class and override init_model method for training SWIN transformers. FYI I recommend you check DINO for training vision transformers. SWaV is not the best candidate.

from lightning-bolts.

SWAV is already implemented in lightning bolts. You will have to inherent SWAV class and override init_model method for training SWIN transformers. FYI I recommend you check DINO for training vision transformers. SWaV is not the best candidate.

But when I override the init_model I will also need to modify SWIN architecture by

• Splitting the default forward function into forward_backbone and forward_head
• Add a new forward which calls both of them
• Add prototype layer and conditions for projection head in the model init

So I added the modified SWIN in swin_swav.py and instead of overriding the init_model, I just added them as arch options to be chosen for ease of use.

from lightning-bolts.