def METHOD_NAME(data_root: str, semantickitti_root: str):
    # Pointcloud files
    pcl_filenames = [
            os.path.join(semantickitti_root, "infer_data", "seq08_f000000.bin"),
            os.path.join(semantickitti_root, "infer_data", "seq08_f000010.bin"),
        ]
    point_clouds = [SemanticKittiDataset.load_point_cloud(f) for f in pcl_filenames]
    config_file = Path(sys.modules[EfficientLpsLearner.__module__].__file__).parent / 'configs' / 'singlegpu_semantickitti.py'
    learner = EfficientLpsLearner(str(config_file))
    learner.load(path=f'{data_root}/checkpoints/model_semantickitti.pth')
    predictions = learner.infer(point_clouds)
    for point_cloud, prediction in zip(point_clouds, predictions):
        EfficientLpsLearner.visualize(point_cloud, (prediction[0], prediction[1]))