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import torch
import torch.nn.functional as F
def hinge_d_loss(logits_real, logits_fake):
loss_real = torch.mean(F.relu(1.0 - logits_real))
loss_fake = torch.mean(F.relu(1.0 + logits_fake))
d_loss = 0.5 * (loss_real + loss_fake)
return d_loss
def vanilla_d_loss(logits_real, logits_fake):
d_loss = 0.5 * (
torch.mean(torch.nn.functional.softplus(-logits_real))
+ torch.mean(torch.nn.functional.softplus(logits_fake))
)
return d_loss
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