def METHOD_NAME(param: Tensor, old_param_device: Optional[int]) -> int:
    r"""This helper function is to check if the parameters are located
    in the same device. Currently, the conversion between model parameters
    and single vector form is not supported for multiple allocations,
    e.g. parameters in different GPUs, or mixture of CPU/GPU.
    The method is consistent with PyTorch.
    The documentation is referenced from:
    https://pytorch.org/docs/1.10/nn.html#utilities.
    Args:
        param ([Tensor]): a Tensor of a parameter of a model
        old_param_device (int): the device where the first parameter of a
                                model is allocated.
    Returns:
        old_param_device (int): report device for the first time
    """
    # Meet the first parameter
    if old_param_device is None:
        old_param_device = param.get_device() if param.is_cuda else -1
    else:
        warn = False
        if param.is_cuda:  # Check if in same GPU
            warn = param.get_device() != old_param_device
        else:  # Check if in CPU
            warn = old_param_device != -1
        if warn:
            raise TypeError(
                "Found two parameters on different devices, "
                "this is currently not supported."
            )
    return old_param_device