Transformer Implementation

A Pytorch Implementation of the paper "Attention is All You Need".
I checked out several popular implementations and I have found a few points which was quite different from the original paper.
This repository is the result of fixing errors and cleaning codes in pytorch-OOP manner.

Examples

• Trained on 20k Korean-English parallel corpus for two hours with general GPU.
• These test sentences are not from the train corpus.
• Hyperparameters
  • d_model = 32
  • d_ff = 128
  • n_layers = 3
  • n_heads = 2

우리 내일 어디로 갈까?
<sos> where should we go tomorrow ? <eos>
너 나 좋아하니?
<sos> do you like to go ? <eos>
이번 시험에서 내가 잘할 수 있을까요?
<sos> can i get a good job this exam ? <eos>
정말 이번에는 졸업하고 싶은데 잘 될지 걱정이야.
<sos> i want to graduate this time , but i 'm worried about you . <eos>

References

• Attention Is All You Need, Vaswani et al.
• The Annotated Transformer, Harvard NLP.
• Attention is all you need: A Pytorch Implementation, Yu-Hsiang Huang
• A Transformer Implementation of Attention is All You Need, Kyubyoung Park
• Transformers, Huggingface

Author

• This repository is developed and maintained by Yonghee Cheon (yonghee.cheon@gmail.com).
• It can be found here: https://github.com/yonghee12/transformer_torch
• Linkedin Profile: https://www.linkedin.com/in/yonghee-cheon-7b90b116a/