HyperGAN
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HyperGAN
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Standard Loss
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criterion = torch.nn.BCEWithLogitsLoss()
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g_loss = criterion(d_fake, torch.ones_like(d_fake))
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d_loss = criterion(d_real, torch.ones_like(d_real)) + criterion(d_fake, torch.zeros_like(d_fake))
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1
{
2
"class": "class:hypergan.losses.standard_loss.StandardLoss"
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}
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Wasserstein Loss
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