code: def accuracy(output, target, topk=(1,)):
      """Computes the precision@k for the specified values of k"""
      maxk = max(topk)
      batch_size = target.size(0)
  
      _, pred = output.topk(maxk, 1, True, True)
      pred = pred.t()
      correct = pred.eq(target.view(1, -1).expand_as(pred))
  
      res = []
      for k in topk:
          correct_k = correct[:k].view(-1).float().sum(0)
          res.append(correct_k.mul_(100.0 / batch_size))
      return res
  
imports: from __future__ import print_function, division, absolute_import
  import argparse
  import os
  import shutil
  import time
  import torch
  import torch.nn
  import torch.nn.parallel
  import torch.backends.cudnn
  import torch.optim
  import torch.utils.data
  import torchvision.transforms
  import torchvision.datasets
  import sys
  import pretrainedmodels
  import pretrainedmodels.utils
label_desc: Use image node_id 6 for calling a global function with example usage: accuracy(output, target, topk) and returns: res