def METHOD_NAME(filename, dimension, classes=2, data_feature_name="data"):
    cur_class = randint(0, classes - 1)
    loc = int(cur_class - (classes / 2))
    arr = np.random.normal(loc=loc, size=(dimension,))
    feature = {"labels": label_feature(cur_class), data_feature_name: string_feature(arr)}
    example = tf.train.Example(features=tf.train.Features(feature=feature))
    with open(filename, "wb") as f:
        f.write(example.SerializeToString())