code: def topk_accuracies(preds, labels, ks):
      """
      Computes the top-k accuracy for each k.
      Args:
          preds (array): array of predictions. Dimension is N.
          labels (array): array of labels. Dimension is N.
          ks (list): list of ks to calculate the top accuracies.
      """
      num_topks_correct = topks_correct(preds, labels, ks)
      return [(x / preds.size(0)) * 100.0 for x in num_topks_correct]
  
label_desc: Use image node_id 3 for calling a global function with example usage: topk_accuracies(preds, labels, ks) and returns: unknown