code: def accuracy(output, target, topk=(1,)):
      """Computes the accuracy over the k top predictions for the specified values of k"""
      maxk = min(max(topk), output.size()[1])
      batch_size = target.size(0)
      _, pred = output.topk(maxk, 1, True, True)
      pred = pred.t()
      correct = pred.eq(target.reshape(1, -1).expand_as(pred))
      return [
          correct[: min(k, maxk)].reshape(-1).float().sum(0)
          * 100.0
          / batch_size
          for k in topk
      ]
  
label_desc: Use image node_id 1 for calling a global function with example usage: accuracy(output, target, topk) and returns: unknown