How to use the memcnn.experiment.manager.ExperimentManager function in memcnn

def run_experiment(experiment_tags, data_dir, results_dir, start_fresh=False, use_cuda=False, workers=None,
                   experiments_file=None, *args, **kwargs):
    if not os.path.exists(data_dir):
        raise RuntimeError('Cannot find data_dir directory: {}'.format(data_dir))

    if not os.path.exists(results_dir):
        raise RuntimeError('Cannot find results_dir directory: {}'.format(results_dir))

    cfg = load_experiment_config(experiments_file, experiment_tags)
    logger.info(cfg)

    model, optimizer, trainer, trainer_params = experiment_config_parser(cfg, workers=workers, data_dir=data_dir)

    experiment_dir = os.path.join(results_dir, '_'.join(experiment_tags))
    manager = ExperimentManager(experiment_dir, model, optimizer)
    if start_fresh:
        logger.info('Starting fresh option enabled. Clearing all previous results...')
        manager.delete_dirs()
    manager.make_dirs()

    if use_cuda:
        manager.model = manager.model.cuda()
        import torch.backends.cudnn as cudnn
        cudnn.benchmark = True

    last_iter = manager.get_last_model_iteration()
    if last_iter > 0:
        logger.info('Continue experiment from iteration: {}'.format(last_iter))
        manager.load_train_state(last_iter)

    trainer_params.update(kwargs)