code: def normalize_features(features):
      """Row-normalize feature matrix."""
      rowsum = np.array(features.sum(1))
      r_inv = np.power(rowsum, -1).flatten()
      r_mat_inv = sp.diags(r_inv)
      features = r_mat_inv.dot(features)
      return features
  
file_path: neural-structured-learning/research/gnn-survey/utils.py
imports: import os
  from models import GAT
  from models import GCN
  from models import GIN
  import numpy
  import scipy.sparse
  import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: normalize_features(features) and returns: features