def METHOD_NAME(test_data_dir, prefix, names, data_list):
    if isinstance(data_list, torch.autograd.Variable) or isinstance(data_list, torch.Tensor):
        data_list = [data_list]
    for i, d in enumerate(data_list):
        d = d.data.cpu().numpy()
        save_tensor_proto(os.path.join(test_data_dir, '{0}_{1}.pb'.format(prefix, i)), names[i], d)