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Pytorch implementation of Wasserstein GANs with Gradient Penalty

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Thanks for sharing this repo. Running the code (`main.py`, 200 epochs, parameters as mentioned in readme, only fixing the the issue mentioned in #1), I couldn't reproduce the results shown...

I can't Reappearance that Results like issue 4. And I find it that this gif what my model generated 6.60Mb, But in this code example gif folder,it is 8.22 Mb....

The self.img_size[0]/16 needs to be typecasted to int: `class Generator(nn.Module): def __init__(self, img_size, latent_dim, dim): super(Generator, self).__init__() self.dim = dim self.latent_dim = latent_dim self.img_size = img_size self.feature_sizes = (int(self.img_size[0] /...