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  • Rank 328,662 (Top 7 %)
  • Language
    Python
  • License
    MIT License
  • Created about 8 years ago
  • Updated about 4 years ago

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Repository Details

A smoother activation function (undergrad code)

Gaussian Error Linear Units (GELUs)

This software allows users to reproduce the results in Gaussian Error Linear Units (GELUs), Dan Hendrycks and Kevin Gimpel 2016.

GELU Approximations

The sigmoid(1.702 * x) * x approximation is fast but is somewhat inaccurate. Meanwhile 0.5 * x * (1 + tanh(x * 0.7978845608 * (1 + 0.044715 * x * x))) is slower but more accurate.

However, exact versions are now available in pytorch, so approximations are no longer necessary for suitable speed.

Execution

Please install Tensorflow, Lasagne, and Python 3+.

Citation

If you find this useful in your research, please consider citing:

@article{hendrycks2016gelu,
  title={Gaussian Error Linear Units (GELUs)},
  author={Hendrycks, Dan and Gimpel, Kevin},
  journal={arXiv preprint arXiv:1606.08415},
  year={2016}
}