code: def aggregate(features, adj, times):
      dtype = features.dtype
      for i in range(times):
          features = adj * features
      return features.astype(dtype)
  
file_path: dgl/examples/pytorch/hilander/utils/misc.py
imports: import json
  import os
  import pickle
  import random
  import time
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: aggregate(features, adj, times) and returns: features