code: def accuracy(output, target, topk=(1, 5)):
      """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()
      # one-hot case
      if target.ndimension() > 1:
          target = target.max(1)[1]
  
      correct = pred.eq(target.view(1, -1).expand_as(pred))
  
      res = dict()
      for k in topk:
          correct_k = correct[:k].reshape(-1).float().sum(0)
          res["acc{}".format(k)] = correct_k.mul_(
              1.0 / batch_size
          ).item()
      return res
  
file_path: nni/examples/nas/legacy/oneshot/spos/utils.py
imports: import torch
  import torch.nn
  import numpy
  import PIL
label_desc: Use image node_id 1 for calling a global function with example usage: accuracy(output, target, topk) and returns: res