ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks
Code is in early release and may be subject to change. Please feel free to open an issue in case of questions.
Overview
We propose 3 strategies to linearly expand a compact network. An expanded network can then be contracted back to the compact one algebraically.
Image Classification
Here are code for image classification experiments on CIFAR-10, CIFAR-100 and ImageNet.
Details on each experiment are listed in corresponding README.md in each folder.
Dummy test
We provide some toy code to expand a convolutional layer with either standard or depthwise convolutions and contract the expanded layers back.
Code in dummy_test.py is same as it in our supplementary material, which can be run simply.
python dummy_test.py