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I found that there is no weight clipping in the paper Least Squares Generative Adversarial Networks. The weight clipping is used in the paper Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities. Obviously, your code is the former.
I tried both situations, and the performance is better without weight clipping.
Thank you for sharing your codes.
I found that there is no weight clipping in the paper Least Squares Generative Adversarial Networks. The weight clipping is used in the paper Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities. Obviously, your code is the former.
I tried both situations, and the performance is better without weight clipping.
I changed the network structure and adjusted the super-parameters to apply to data cifar-10. I thought maybe someone needed it, so I left the url of my code.
https://github.com/AliceAria/Performance-comparison-of-GAN-on-cifar-10
Thanks again.
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