dd9512019c67fdb06c0e53991608d36ca5cdf920,loss.py,GeneratorAdversarialWithContentLoss,forward,#GeneratorAdversarialWithContentLoss#,38

Before Change

        features_target = self.loss_network(target_images)
        content_loss = self.mse_loss(features_input, features_target)
        image_loss = self.mse_loss(out_images, target_images)
        g_tv_loss = (((out_images[:, :, :-1, :] - out_images[:, :, 1:, :]) ** 2 + (
        out_images[:, :, :, :-1] - out_images[:, :, :, 1:]) ** 2) ** 1.25).mean()
        if self.using_l1:
            // L1 Loss

After Change

    def forward(self, out_labels, out_images, target_images):
        // Adversarial Loss
        adversarial_loss = torch.mean(torch.log(1 - out_labels))
        // Content Loss
        features_input = self.loss_network(out_images)
        features_target = self.loss_network(target_images)

Instances