'''simple docstring'''






from __future__ import annotations





def    _SCREAMING_SNAKE_CASE		(			__snake_case       : list[list[int]]      ,		__snake_case       : list[list[int]]							):
     assert len(__snake_case							) == len(__snake_case							)

     _A								=     len(__snake_case							)
     _A								=     list(range(__snake_case							)							)
     _A								=     [-1] * n  # who the donor has donated to
     _A								=     [-1] * n  # who the recipient has received from
     _A								=     [0] * n

     while unmatched_donors:
          _A								=     unmatched_donors[0]
          _A								=     donor_pref[donor]
          _A								=     donor_preference[num_donations[donor]]
          num_donations[donor] += 1
          _A								=     recipient_pref[recipient]
          _A								=     rec_record[recipient]

          if prev_donor != -1:
               if rec_preference.index(__snake_case							) > rec_preference.index(__snake_case							):
                    _A								=     donor
                    _A								=     recipient
                    unmatched_donors.append(__snake_case							)
                    unmatched_donors.remove(__snake_case							)
          else:
               _A								=     donor
               _A								=     recipient
               unmatched_donors.remove(__snake_case							)
     return donor_record




'''simple docstring'''






from sklearn.neural_network import MLPClassifier

_UpperCAmelCase						:    str     					=					[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
_UpperCAmelCase						:    Any     					=					[0, 1, 0, 0]


_UpperCAmelCase						:    List[Any]     					=					MLPClassifier(
    solver='''lbfgs''', alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


_UpperCAmelCase						:    Optional[Any]     					=					[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
_UpperCAmelCase						:    Tuple     					=					clf.predict(test)





def    _SCREAMING_SNAKE_CASE		(			__snake_case       : Optional[Any]							):
     return list(__snake_case							)


if __name__ == "__main__":
   import doctest

   doctest.testmod()



