https://github.com/openai/weightnorm
Example code for Weight Normalization, from "Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks"
https://github.com/openai/weightnorm
paper
Last synced: 2 months ago
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Example code for Weight Normalization, from "Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks"
- Host: GitHub
- URL: https://github.com/openai/weightnorm
- Owner: openai
- License: mit
- Created: 2016-12-03T15:54:26.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2018-11-22T00:36:32.000Z (over 6 years ago)
- Last Synced: 2025-03-30T15:11:08.542Z (2 months ago)
- Topics: paper
- Language: Python
- Homepage: https://arxiv.org/abs/1602.07868
- Size: 15.6 KB
- Stars: 364
- Watchers: 165
- Forks: 117
- Open Issues: 12
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
**Status:** Archive (code is provided as-is, no updates expected)
# Weight Normalization
This repo contains example code for [Weight Normalization](https://arxiv.org/abs/1602.07868), as described in the following
paper:
**Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks**, by
Tim Salimans, and Diederik P. Kingma.
- The folder 'lasagne' contains code using the Lasagne package for Theano. This code was used to run the CIFAR-10 experiments in the paper.
- The folder 'tensorflow' contains a single nn.py file with a direct implementation copied from our [PixelCNN++](https://github.com/openai/pixel-cnn) repository.
- The folder 'keras' contains example code for use with the Keras package.
## Citation
If you find this code useful please cite us in your work:
```
@inproceedings{Salimans2016WeightNorm,
title={Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks},
author={Tim Salimans and Diederik P. Kingma},
booktitle={Neural Information Processing Systems 2016},
year={2016}
}
```