i edited .view() to .reshape() but same error still occured…
def accuracy(output, target, topk=(1,)):
  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].reshape(-1).float().sum(0)
    res.append(correct_k.mul_(100.0/batch_size))
  return res

full error sentence:
RuntimeError: view size is not compatible with input tensor’s size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(…) instead.
i don’t know why it still cry an error like this…