Official implementation of cosformer-attention in cosFormer: Rethinking Softmax in Attention

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Deep Learning cosFormer
Overview

cosFormer

Official implementation of cosformer-attention in cosFormer: Rethinking Softmax in Attention

Update log

  • 2022/2/28
    • Add core code

License

This repository is released under the Apache 2.0 license as found in the LICENSE file.

Citation

If you use this code for a paper, please cite:

@inproceedings{
  zhen2022cosformer,
  title={cosFormer: Rethinking Softmax In Attention},
  author={Zhen Qin and Weixuan Sun and Hui Deng and Dongxu Li and Yunshen Wei and Baohong Lv and Junjie Yan and Lingpeng Kong and Yiran Zhong},
  booktitle={International Conference on Learning Representations},
  year={2022},
  url={https://openreview.net/forum?id=Bl8CQrx2Up4}
}
Comments
  • causal attention not working when q and kv are not in same length

    causal attention not working when q and kv are not in same length

    Thank you for your great work! I am currently working on a seq2seq task and I found the causal attention code only works the src_len and the tgt_len are the same. Also, I suggest that you could adopt EPFL's causal linear attention CUDA code to improve the speed of causal attention.

    opened by zero0kiriyu 1
  • Question about space complexity

    Question about space complexity

    Thanks very much for your interesting work! I have a question about the O(N) space complexity mentioned in your paper. I am wondering whether you can help me to figure it out.

    In Eq. (11) of your paper, you compute QK^T in the denominator, which may lead to O(N^2*d) space complexity?

    bests

    opened by nihaomiao 0
  • Why cosformer not work on XL-base transformer architecture?

    Why cosformer not work on XL-base transformer architecture?

    When implementing cosformer on MultiHeadAttention in Transformer-XL and running without extra long-range memory, the ReLU performance is worse than eLU. I think it is because the Attention and FF Net are different since XL-like transformer has different layer norm and residual connection. Why this ReLU(Q)ReLU(K).T softmax replacement is not robust on different transformer architectures?

    opened by lwaekfjlk 0
  • Pre-train model

    Pre-train model

    In the paper，it mentioned that the work of the bidirectional language modeling pre-train has been done. Are you planning on releasing some pre-trained weights for the model?

    opened by csorujian 0
  • Attn Mask for Non-causal Models

    Attn Mask for Non-causal Models

    We are examining non-NLP applications of the cosformer self-attention, and would need to use attention masking for the padded tokens in the batch. Is there a way to incorporate this ? Because the code does not explicitly compute the attention weights on which masking is traditionally applied.

    opened by roshansh-cmu 1
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