def METHOD_NAME(self, dtype, model_size):
    if ("amd" in pytest.cpu_vendor) and (dtype == torch.half):
        pytest.skip("cpu-adam with half precision not supported on AMD CPUs")
    from deepspeed.ops.adam import DeepSpeedCPUAdam
    cpu_data = torch.randn(model_size, device='cpu').to(dtype)
    cpu_param = torch.nn.Parameter(cpu_data)
    cuda_param = torch.nn.Parameter(cpu_data.to(get_accelerator().device_name()))
    # tolerance = cpu_param.float().norm().detach().numpy() * 1e-2
    # check_equal(cpu_param.float().norm(),
    #             cuda_param.float().cpu().norm(),
    #             atol=tolerance,
    #             verbose=True)
    cpu_optimizer = DeepSpeedCPUAdam([cpu_param])
    cuda_optimizer = FusedAdam([cuda_param])
    _compare_optimizers(model_size=model_size,
                        param1=cpu_param,
                        optimizer1=cpu_optimizer,
                        param2=cuda_param,
                        optimizer2=cuda_optimizer)