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SGAN: Structured Generative Adversarial Networks
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utils Initial version Mar 30, 2017


This repo provides codes for "Structured Generative Adversarial Networks" and is based on TripleGAN.

For example, you can run python -u -ssl_seed 1 to reproduce the semi-supervised classification results on CIFAR-10 dataset.

You can run python -u -oldmodel ... to generate samples, infer latent codes and transfer image styles based on a trained model.

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