code: def nmi(gt_labels, pred_labels):
      return normalized_mutual_info_score(pred_labels, gt_labels)
  
file_path: dgl/examples/pytorch/hilander/utils/metrics.py
imports: from __future__ import division
  import numpy
  from sklearn.metrics import precision_score, recall_score
  from sklearn.metrics.cluster import contingency_matrix, normalized_mutual_info_score
label_desc: Use image node_id 7 for calling a global function with example usage: nmi(gt_labels, pred_labels) and returns: normalized_mutual_info_score