This repository contains the code for Convolutional Neural Tangent Kernel (CNTK) in the following paper
On Exact Computation with an Infinitely Wide Neural Net (NeurIPS 2019)
@inproceedings{arora2019exact,
title={On exact computation with an infinitely wide neural net},
author={Arora, Sanjeev and Du, Simon S. and Hu, Wei and Li, Zhiyuan and Salakhutdinov, Ruslan and Wang, Ruosong},
booktitle={Thirty-third Conference on Neural Information Processing Systems},
year={2019}
}
Require Python 2.7 and CUDA.
- Install CuPy.
- Download CIFAR-10.
wget https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz; tar zxvf cifar-10-python.tar.gz
- Parallelize Line 143-146 in CNTK.py according to your specific computing enviroment to utilize multiple GPUs.
To reproduce results in Table 1 in our paper:
For column CNTK-V:
python CNTK.py --gap no --fix no --depth DEPTH
where DEPTH is 3, 4, 6, 11 or 21.
For column CNTK-GAP:
python CNTK.py --gap yes --fix yes --depth DEPTH
where DEPTH is 3, 4, 6, 11 or 21.
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