Giter VIP home page Giter VIP logo

attn2d's Introduction

This is a fork of Fairseq(-py) with implementations of the following models:

Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction

An NMT models with two-dimensional convolutions to jointly encode the source and the target sequences.

Pervasive Attention also provides an extensive decoding grid that we leverage to efficiently train wait-k models.

See README.

Efficient Wait-k Models for Simultaneous Machine Translation

Transformer Wait-k models (Ma et al., 2019) with unidirectional encoders and with joint training of multiple wait-k paths.

See README.

Fairseq Requirements and Installation

  • PyTorch version >= 1.4.0
  • Python version >= 3.6
  • For training new models, you'll also need an NVIDIA GPU and NCCL

Installing Fairseq

git clone https://github.com/elbayadm/attn2d
cd attn2d
pip install --editable .

License

fairseq(-py) is MIT-licensed. The license applies to the pre-trained models as well.

Citation

For Pervasive Attention, please cite:

@InProceedings{elbayad18conll,
    author ="Elbayad, Maha and Besacier, Laurent and Verbeek, Jakob",
    title = "Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction",
    booktitle = "Proceedings of the 22nd Conference on Computational Natural Language Learning",
    year = "2018",
 }

For our wait-k models, please cite:

@article{elbayad20waitk,
    title={Efficient Wait-k Models for Simultaneous Machine Translation},
    author={Elbayad, Maha and Besacier, Laurent and Verbeek, Jakob},
    journal={arXiv preprint arXiv:2005.08595},
    year={2020}
}

For Fairseq, please cite:

@inproceedings{ott2019fairseq,
  title = {fairseq: A Fast, Extensible Toolkit for Sequence Modeling},
  author = {Myle Ott and Sergey Edunov and Alexei Baevski and Angela Fan and Sam Gross and Nathan Ng and David Grangier and Michael Auli},
  booktitle = {Proceedings of NAACL-HLT 2019: Demonstrations},
  year = {2019},
}

attn2d's People

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.