code: def _centroids(n_clusters: int, points: List[List[float]]) -> List[List[float]]:
      
  
      k_means = KMeans(n_clusters=n_clusters)
      k_means.fit(points)
  
      closest, _ = pairwise_distances_argmin_min(k_means.cluster_centers_, points)
  
      return list(map(list, np.array(points)[closest.tolist()]))
docs: Return n_clusters centroids of points