TMLR 2023
Dual PatchNorm
Abstract
We propose Dual PatchNorm: two Layer Normalization layers (LayerNorms), before and after the patch embedding layer in Vision Transformers. We demonstrate that Dual PatchNorm outperforms the result of exhaustive search for alternative LayerNorm placement strategies in the Transformer block itself. In our experiments on image classification and contrastive learning, incorporating this trivial modification, often leads to improved accuracy over well-tuned vanilla Vision Transformers and never hurts.
Authors
Keywords
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Context
- Venue
- Transactions on Machine Learning Research
- Archive span
- 2022-2026
- Indexed papers
- 3849
- Paper id
- 311274513419195915