def METHOD_NAME(local_ds: Dataset, point_cloud_paths):
    for compression, path in point_cloud_paths.items():
        if compression == "las":
            dummy = np.zeros((20153, 3))
        local_ds.create_tensor(
            "point_cloud", htype="point_cloud", sample_compression=compression
        )
        local_ds.point_cloud.append(deeplake.read(path))
        assert local_ds.point_cloud[0][0:5].numpy().shape == dummy[0:5].shape
        assert local_ds.point_cloud[0][100:120].numpy().shape == dummy[100:120].shape
        assert local_ds.point_cloud[0][120].numpy().shape == dummy[120].shape
        assert local_ds.point_cloud[0][-1].numpy().shape == dummy[-1].shape
        assert local_ds.point_cloud[0][10:5:-2].numpy().shape == dummy[10:5:-2].shape
        assert (
            local_ds.point_cloud[0][-3:-10:-1].numpy().shape == dummy[-3:-10:-1].shape
        )
        assert (
            local_ds.point_cloud[0][-25:100:-2].numpy().shape == dummy[-25:100:-2].shape
        )
        assert local_ds.point_cloud[0][::-1].numpy().shape == dummy[::-1].shape
        assert local_ds.point_cloud[0][:5:-1].numpy().shape == dummy[:5:-1].shape
        assert local_ds.point_cloud[0][-1].numpy().shape == dummy[-1].shape
        return