def METHOD_NAME(self):
    def model(x, y):
        return (x + y) * y
    @torch._dynamo.optimize("cudagraphs")
    def fn(x, y):
        for i in range(N_ITERS):
            loss = model(x, y).sum()
            loss.backward()
    x = torch.randn(3, device="cuda", requires_grad=True)
    y = torch.randn(3, device="cuda")
    fn(x, y)