code: def is_l2norm(features, size):
      rand_i = random.choice(range(size))
      norm_ = np.dot(features[rand_i, :], features[rand_i, :])
      return abs(norm_ - 1) < 1e-6
  
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 3 for calling a global function with example usage: is_l2norm(features, size) and returns: unknown