840e02d43c5724847f767d6bc82981b3aed5eaa6,hypergan/train_hooks/gradient_penalty_train_hook.py,GradientPenaltyTrainHook,forward,#GradientPenaltyTrainHook#,17

Before Change

    d = self.gan.discriminator(interpolated)

    grad = torch_grad(outputs=d, inputs=interpolated,
                               grad_outputs=torch.ones(d.size()).cuda(),
                               create_graph=True, retain_graph=True)[0]

    grad = grad.view(self.gan.batch_size(), -1) 

After Change

    grad = torch_grad(outputs=d.mean(), inputs=parameters, create_graph=True, retain_graph=True)

    grad = [_g.view(-1) for _g in grad]
    grad_loss = [((torch.sqrt(torch.sum(_g**2, dim=0) +1e-12) - 1) ** 2).mean() for _g in grad]
    grad_loss = sum(grad_loss)

    loss = gamma*grad_loss
    return [loss, loss]

Instances