code: def check_class_labels(*args: BaseEstimator) -> bool:
      """
      Checks the known class labels for each classifier.
  
      Args:
          *args: Classifier objects to check the known class labels.
  
      Returns:
          True, if class labels match for all classifiers, False otherwise.
      """
      try:
          classes_ = [estimator.classes_ for estimator in args]
      except AttributeError:
          raise NotFittedError(
              "Not all estimators are fitted. Fit all estimators before using this method."
          )
  
      for classifier_idx in range(len(args) - 1):
          if not np.array_equal(
              classes_[classifier_idx], classes_[classifier_idx + 1]
          ):
              return False
  
      return True
  
imports: from typing import Sequence
  import numpy
  from sklearn.base import BaseEstimator
  from sklearn.exceptions import NotFittedError
label_desc: Use image node_id 1 for calling a global function with example usage: check_class_labels() and returns: True, False