code: def __str__(self):
      acc_global, acc, iu = self.compute()
      return (
          "global correct: {:.1f}\n"
          "average row correct: {}\n"
          "IoU: {}\n"
          "mean IoU: {:.1f}"
      ).format(
          acc_global.item() * 100,
          ["{:.1f}".format(i) for i in (acc * 100).tolist()],
          ["{:.1f}".format(i) for i in (iu * 100).tolist()],
          iu.mean().item() * 100,
      )
  
imports: from collections import defaultdict, deque
  import datetime
  import time
  import torch
  import torch.distributed
  import errno
  import os
label_desc: Use image node_id 6 for calling the ConfusionMatrix obj's underlying member method code with example usage: obj.__str__() and returns: str