code: def get_cluster_labels(self, query, query_labels, **kwargs):
      num_clusters = len(torch.unique(query_labels.flatten()))
      return self.kmeans_func(query, num_clusters)
  
imports: import torch
  from sklearn.metrics import adjusted_mutual_info_score, normalized_mutual_info_score
  from .None import common_functions
  from .inference import FaissKMeans, FaissKNN
label_desc: Use image node_id 6 for calling the AccuracyCalculator obj's underlying member method code with example usage: obj.get_cluster_labels(query, query_labels) and returns: self