In order to `torch.load()` a GPU-trained model onto a CPU (or specific GPU),
    you have to supply a `map_location` function. Call this with
    the desired `cuda_device` to get the function that `torch.load()` needs.

def device_mapping(cuda_device: int):
    """
    In order to `torch.load()` a GPU-trained model onto a CPU (or specific GPU),
    you have to supply a `map_location` function. Call this with
    the desired `cuda_device` to get the function that `torch.load()` needs.
    """

    def inner_device_mapping(storage: torch.Storage, location) -> torch.Storage:  # pylint: disable=unused-argument
        if cuda_device >= 0:
            return storage.cuda(cuda_device)
        else:
            return storage

    return inner_device_mapping