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The original paper states that contrastive learning helps transfer learning.
But, to my understanding, in the above code, this operation does not perform contrastive learning over multi-domain and it seems to simply perform contrastive learning over single-domain.
To perform contrastive learning over multi-domain, I think I need to change the code in the following, right? loss_x = F.cross_entropy(output_x[:, :-self.n_cls], label)
The text was updated successfully, but these errors were encountered:
Thanks for your very interesting research.
I have some questions about the code of L402 in
trainers/dapl.py
DAPrompt/trainers/dapl.py
Line 402 in f24b0c1
The original paper states that contrastive learning helps transfer learning.
But, to my understanding, in the above code, this operation does not perform contrastive learning over multi-domain and it seems to simply perform contrastive learning over single-domain.
To perform contrastive learning over multi-domain, I think I need to change the code in the following, right?
loss_x = F.cross_entropy(output_x[:, :-self.n_cls], label)
The text was updated successfully, but these errors were encountered: