def METHOD_NAME(input_file, label_file, n, n_his, n_pred, n_config):
    """data processing
    """
    # data
    x = pd.read_csv(input_file)
    y = pd.read_csv(label_file)
    x = x.drop(columns=['date'])
    y = y.drop(columns=['date'])
    # param
    n_val, n_test = n_config
    n_train = len(y) - n_val - n_test - 2
    # (?,26,74,1)
    df = pd.DataFrame(columns=x.columns)
    for i in range(len(y) - n_pred + 1):
        df = df.append(x[i:i + n_his])
        df = df.append(y[i:i + n_pred])
    data = df.values.reshape(-1, n_his + n_pred, n, 1)
    x_stats = {'mean': np.mean(data), 'std': np.std(data)}
    x_train = data[:n_train]
    x_val = data[n_train:n_train + n_val]
    x_test = data[n_train + n_val:]
    x_data = {'train': x_train, 'val': x_val, 'test': x_test}
    dataset = Dataset(x_data, x_stats)
    return dataset