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import torch
import torch.nn.functional as F
def exp_d_loss(logits_real, logits_fake):
loss_real = torch.mean(torch.exp(-logits_real))
loss_fake = torch.mean(torch.exp(logits_fake))
d_loss = 0.5 * (loss_real + loss_fake)
return d_loss
def hinge_d_loss(logits_real, logits_fake):
loss_real = torch.mean(F.relu(1. - logits_real))
loss_fake = torch.mean(F.relu(1. + 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(F.softplus(-logits_real)) +
torch.mean(F.softplus(logits_fake)))
return d_loss |