How to use the hdbscan.prediction function in hdbscan

min_samples=self.min_samples,
                prediction_data=True,
            ).fit(self.embeddings)

            # Assign soft clusters to embeddings
            self.soft_clusters = hdbscan.all_points_membership_vectors(clusterer)

            # Store clusterer in S3
            store_on_s3(clusterer, self.s3_bucket, self.clusterer_name)
        else:
            logging.info("Loading fitted HDBSCAN from S3.")
            # Load clusterer from S3
            clusterer = load_from_s3(self.s3_bucket, self.clusterer_name)

            # Predict soft labels
            self.soft_clusters = hdbscan.prediction.membership_vector(
                clusterer, np.array(self.embeddings)
            )

        # Group arXiv paper IDs with clusters
        id_clusters_mapping = self._create_mappings(
            self.ids, self.soft_clusters, "clusters"
        )
        # Store mapping in DB
        s.bulk_insert_mappings(ArticleCluster, id_clusters_mapping)
        s.commit()
        self.next(self.end)