





from __future__ import annotations


def      SCREAMING_SNAKE_CASE      (   lowerCAmelCase     ,							lowerCAmelCase       ):
       assert len(lowerCAmelCase       ) == len(lowerCAmelCase       )

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

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

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














"""simple docstring"""





import torch

from transformers import PreTrainedModel

from .custom_configuration import CustomConfig, NoSuperInitConfig
class  __lowerCamelCase     (	_a	):
   a   :					List[Any]			    =CustomConfig

   def __init__(       self			,					snake_case_   )		->							str:
       super().__init__(snake_case_   )
       UpperCamelCase__								=     torch.nn.Linear(config.hidden_size			,					config.hidden_size   )

   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							Optional[int]:
       return self.linear(snake_case_   )







   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							Union[str, Any]:
       pass







class  __lowerCamelCase     (	_a	):
   a   :					Optional[int]			    =NoSuperInitConfig

   def __init__(       self			,					snake_case_   )		->							Optional[int]:
       super().__init__(snake_case_   )
       UpperCamelCase__								=     torch.nn.Linear(config.attribute			,					config.attribute   )

   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							int:
       return self.linear(snake_case_   )







   def     SCREAMING_SNAKE_CASE__			(       self			,					snake_case_   )		->							Union[str, Any]:
       pass




