def style_noise(self, y, style):
    n = torch.randn(y.shape)
    for i in range(n.shape[0]):
        n[i] = (n[i] - n.mean(dim=(1, 2, 3))[i]) * style.std(dim=(1, 2, 3))[i] / n.std(dim=(1, 2, 3))[i] + style.mean(dim=(1, 2, 3))[i]
    noise = Variable(n, requires_grad=False).to(y.device)
return noise