code: def recall(rank, ground_truth, N):
      return len(set(rank[:N]) & set(ground_truth)) / float(
          len(set(ground_truth))
      )
  
file_path: dgl/examples/pytorch/NGCF/NGCF/utility/metrics.py
imports: import numpy
  from sklearn.metrics import roc_auc_score
label_desc: Use image node_id 1 for calling a global function with example usage: recall(rank, ground_truth, N) and returns: unknown