PR Product

Code for ICCV2019 Oral paper "PR Product: A Substitute for Inner Product in Neural Networks", containing PR-FC, PR-CNN and PR-LSTM.

The code is implemented based on Pytorch.

Usage

The usage of PR-X is the same as the one of nn.X:

    import PR
    
    pr_fc = PR.PRLinear(100, 200)
    pr_cnn = PR.PRConv2d(32, 64, kernel_size=3, stride=1, padding=1, bias=False)
    pr_lstmcell = PR.PRLSTMCell(256, 512)

Citing

If you use 'PR Product' in a scientific publication, we would appreciate references to the following paper:

PR Product: A Substitute for Inner Product in Neural Networks. ICCV2019 Oral: PR Product

Biblatex entry:

    @inproceedings{wang2019pr,
                   title={PR Product: A Substitute for Inner Product in Neural Networks},
                   author={Wang, Zhennan and Zou, Wenbin and Xu, Chen},
                   booktitle={Proceedings of the IEEE International Conference on Computer Vision},
                   pages={6013--6022},
                   year={2019}
                   }

License

This code is released under the MIT License (refer to the LICENSE file for details).