code: def get_accruacy_over_list(prediction, groundtruth, **kwargs):
      if type(groundtruth) == list:
          if len(groundtruth) == 0:
              return 0
          return np.max(
              [accuracy(prediction, gt, **kwargs) for gt in groundtruth]
          )
      return accuracy(prediction, groundtruth)
  
file_path: OpenPrompt/openprompt/utils/crossfit_metrics.py
imports: import numpy
  import string
  import re
  from collections import Counter
  from sklearn.metrics import matthews_corrcoef, f1_score
  from scipy.stats import pearsonr, spearmanr
  from rouge import Rouge
label_desc: Use image node_id 6 for calling a global function with example usage: get_accruacy_over_list(prediction, groundtruth) and returns: accuracy, np, int