def loss()

in models/losses/gan_loss.py [0:0]

• 27 lines of code
• 7 McCabe index (conditional complexity)

    def loss(self, input, target_is_real, for_discriminator=True):
        if self.gan_mode == "original":  # cross entropy loss
            target_tensor = self.get_target_tensor(input, target_is_real)
            loss = F.binary_cross_entropy_with_logits(input, target_tensor)
            return loss
        elif self.gan_mode == "ls":
            target_tensor = self.get_target_tensor(input, target_is_real)
            return F.mse_loss(input, target_tensor)
        elif self.gan_mode == "hinge":
            if for_discriminator:
                if target_is_real:
                    minval = torch.min(input - 1, self.get_zero_tensor(input))
                    loss = -torch.mean(minval)
                else:
                    minval = torch.min(-input - 1, self.get_zero_tensor(input))
                    loss = -torch.mean(minval)
            else:
                assert (
                    target_is_real
                ), "The generator's hinge loss must be aiming for real"
                loss = -torch.mean(input)
            return loss
        else:
            # wgan
            if target_is_real:
                return -input.mean()
            else:
                return input.mean()