def METHOD_NAME(root_dir):
    """
    root_dir: directory to the mocked dataset
    """
    mocked_samples = []
    mocked_training = []
    mocked_validation = []
    mocked_testing = []
    sample_rate = 22050
    seed = 0
    for genre in gtzan.gtzan_genres:
        base_dir = os.path.join(root_dir, "genres", genre)
        os.makedirs(base_dir, exist_ok=True)
        for i in range(100):
            filename = f"{genre}.{i:05d}"
            path = os.path.join(base_dir, f"{filename}.wav")
            data = get_whitenoise(sample_rate=sample_rate, duration=0.01, n_channels=1, dtype="int16", seed=seed)
            save_wav(path, data, sample_rate)
            sample = (normalize_wav(data), sample_rate, genre)
            mocked_samples.append(sample)
            if filename in gtzan.filtered_test:
                mocked_testing.append(sample)
            if filename in gtzan.filtered_train:
                mocked_training.append(sample)
            if filename in gtzan.filtered_valid:
                mocked_validation.append(sample)
            seed += 1
    return (mocked_samples, mocked_training, mocked_validation, mocked_testing)