code: def print_summary(name, labels, net_p, lin_p, loss):
      """Print summary information comparing a network with its linearization."""
      print("\nEvaluating Network on {} data.".format(name))
      print("---------------------------------------")
      print("Network Accuracy = {}".format(_accuracy(net_p, labels)))
      print("Network Loss = {}".format(loss(net_p, labels)))
      if lin_p is not None:
          print(
              "Linearization Accuracy = {}".format(
                  _accuracy(lin_p, labels)
              )
          )
          print("Linearization Loss = {}".format(loss(lin_p, labels)))
          print(
              "RMSE of predictions: {}".format(
                  jnp.sqrt(jnp.mean((net_p - lin_p) ** 2))
              )
          )
      print("---------------------------------------")
  
label_desc: Use image node_id 2 for calling a global function with example usage: print_summary(name, labels, net_p, lin_p, loss) without return types