class_docstr: Class for a sample/label pair to be used in a `SortedList`.
code: def __ge__(self, other):
      # This implements >= comparison so we can use this class in a `SortedList`. The `total_ordering` decorator
      # automatically generates the rest of the comparison magic functions based on this one
  
      close_cells = np.isclose(self.key, other.key)
      if np.all(close_cells):
          return True
  
      # If the keys are not exactly the same (up to floating-point inaccuracies), we compare the value of the first
      # index which is not the same to decide on an ordering
  
      compare_idx = np.unravel_index(
          np.argmin(close_cells), shape=self.key.shape
      )
      return self.key[compare_idx] >= other.key[compare_idx]
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  from functools import total_ordering
  import logging
  from typing import Callable, List, Optional, Union, Tuple, TYPE_CHECKING
  import numpy
  from art.estimators.estimator import BaseEstimator
  from art.estimators.regression.regressor import RegressorMixin, Regressor
  from art.estimators.classification import BlackBoxClassifier
label_desc: Use image node_id 3 for calling the FuzzyMapping obj's underlying member method code with example usage: obj.__ge__(other) and returns: unknown, True