code: def sets_accuracy(
      y_true: [list, np.ndarray], y_predicted: [list, np.ndarray]
  ) -> float:
      """
      Calculate accuracy in terms of sets coincidence
  
      Args:
          y_true: true values
          y_predicted: predicted values
  
      Returns:
          portion of samples with absolutely coincidental sets of predicted values
  
      Alias:
          sets_accuracy
      """
      examples_len = len(y_true)
      correct = sum(
          [set(y1) == set(y2) for y1, y2 in zip(y_true, y_predicted)]
      )
      return correct / examples_len if examples_len else 0
  
file_path: DeepPavlov/deeppavlov/metrics/accuracy.py
imports: import itertools
  import re
  from logging import getLogger
  from typing import List
  import numpy
  from deeppavlov.core.common.metrics_registry import register_metric
label_desc: Use image node_id 6 for calling a global function with example usage: sets_accuracy(y_true, y_predicted) and returns: unknown