Code for the regularizer proposed in the NIPS 2017 paper on "Gradient descent GAN optimization is locally stable" arXiv:1706.04156

The code for the Gaussian experiments is based on https://github.com/poolio/unrolled_gan but modified to reflect the parameters specified in the Unrolled GANs paper arxiv:1611.02163. The experiments for our paper were performed on Tensorflow 1.1.0 and Keras 1.2.

Run python <filename>.py where <filename> is either gaussian-toy-unrolled.py or gaussian-toy-regularized.py to run the unrolled GAN and the gradient-norm-regularized GAN respectively.