def METHOD_NAME(min_labels):
    labels_reader = providers.LabelsReader.from_user_instances(min_labels)
    ds = labels_reader.make_dataset()
    example_preaug = next(iter(ds))
    augmenter = augmentation.ImgaugAugmenter.from_config(
        augmentation.AugmentationConfig(
            rotate=True, rotation_min_angle=-90, rotation_max_angle=-90
        )
    )
    ds = augmenter.transform_dataset(ds)
    example = next(iter(ds))
    assert example["image"].shape == (384, 384, 1)
    assert example["image"].dtype == tf.uint8
    np.testing.assert_allclose(
        tf.image.rot90(example_preaug["image"]), example["image"]
    )
    assert example["instances"].shape == (2, 2, 2)
    assert example["instances"].dtype == tf.float32
    # TODO: check for correctness
    assert tf.reduce_all(example["instances"] != example_preaug["instances"])