def METHOD_NAME(self):
    model_size = 64
    device = get_accelerator().device_name(0)  # 'cuda:0' or 'xpu:0'
    param = torch.nn.Parameter(torch.randn(model_size, device=device))
    optimizer = DeepSpeedCPUAdagrad([param])
    param.grad = torch.randn(model_size, device=device)
    with pytest.raises(AssertionError):
        optimizer.step()