
'''simple docstring'''

import torch

from transformers import AutoModel


class      a_     (torch.nn.Module			):




       def __init__(   self      ,      snake_case_="sayef/fsner-bert-base-uncased"     ):
         super(lowercase_      ,      self     ).__init__()

         _lowerCAmelCase				:     int       =    AutoModel.from_pretrained(lowercase_      ,      return_dict=lowercase_     )
         _lowerCAmelCase				:     Optional[int]       =    torch.nn.CosineSimilarity(3      ,      1E-08     )
         _lowerCAmelCase				:     List[str]       =    torch.nn.Softmax(dim=1     )




       def 							__UpperCamelCase				(   self      ,      **snake_case_     ):
         return self.bert(**lowercase_     ).last_hidden_state




       def 							__UpperCamelCase				(   self      ,      snake_case_     ):
         return token_embeddings.sum(2      ,      keepdim=lowercase_     )




       def 							__UpperCamelCase				(   self      ,      snake_case_      ,      snake_case_      ,      snake_case_=1     ):
         return self.softmax(T * self.cos(lowercase_      ,      lowercase_     )     )







       def 							__UpperCamelCase				(   self      ,      snake_case_      ,      snake_case_     ):
         _lowerCAmelCase				:     List[Any]       =    W_supports['''sizes'''].tolist()
         _lowerCAmelCase				:     Dict       =    W_supports['''start_token_id'''].item()
         _lowerCAmelCase				:     Union[str, Any]       =    W_supports['''end_token_id'''].item()

         del W_supports["sizes"]
         del W_supports["start_token_id"]
         del W_supports["end_token_id"]

         _lowerCAmelCase				:     Optional[Any]       =    self.BERT(**lowercase_     )
         _lowerCAmelCase				:     int       =    self.BERT(**lowercase_     )

         _lowerCAmelCase				:     List[str]       =    None
         _lowerCAmelCase				:     Union[str, Any]       =    None

         _lowerCAmelCase				:     int       =    W_supports['''input_ids'''] == start_token_id
         _lowerCAmelCase				:     Optional[Any]       =    W_supports['''input_ids'''] == end_token_id

         for i, size in enumerate(lowercase_     ):
           if i == 0:
             _lowerCAmelCase				:     str       =    0
           else:
             _lowerCAmelCase				:     List[Any]       =    support_sizes[i - 1]

           _lowerCAmelCase				:     Optional[Any]       =    S[s : s + size][start_token_masks[s : s + size]]
           _lowerCAmelCase				:     List[Any]       =    S[s : s + size][end_token_masks[s : s + size]]

           _lowerCAmelCase				:     Union[str, Any]       =    torch.matmul(q[i]      ,      s_start.T     ).sum(1     ).softmax(0     )
           _lowerCAmelCase				:     Any       =    torch.matmul(q[i]      ,      s_end.T     ).sum(1     ).softmax(0     )

           if p_starts is not None:
             _lowerCAmelCase				:     List[Any]       =    torch.vstack((p_starts, p_start)     )
             _lowerCAmelCase				:     List[Any]       =    torch.vstack((p_ends, p_end)     )
           else:
             _lowerCAmelCase				:     Union[str, Any]       =    p_start
             _lowerCAmelCase				:     str       =    p_end

         return p_starts, p_ends





"""simple docstring"""





from __future__ import annotations

import sys
from collections import deque
from typing import Generic, TypeVar

__UpperCamelCase  :      Tuple							      =		TypeVar('''T''')







class 				SCREAMING_SNAKE_CASE					(		Generic[T]       ):






					"""simple docstring"""



					lowercase__				 =       42  # Cache store of keys
					lowercase__				 =       42  # References of the keys in cache
					lowercase__				 =       10  # Maximum capacity of cache







					def __init__(       self			:				Dict   ,lowercase_			:				int		):
						lowerCAmelCase__	:						str  				=	deque()
						lowerCAmelCase__	:						Any  				=	set()
						if not n:
							lowerCAmelCase__	:						Optional[Any]  				=	sys.maxsize
						elif n < 0:
							raise ValueError('''n should be an integer greater than 0.'''		)
						else:
							lowerCAmelCase__	:						int  				=	n







					def        __lowerCAmelCase (       self			:				str   ,lowercase_			:				T		):
						if x not in self.key_reference:
							if len(self.dq_store		) == LRUCache._MAX_CAPACITY:
								lowerCAmelCase__	:						Any  				=	self.dq_store.pop()
								self.key_reference.remove(lowercase_		)
						else:
							self.dq_store.remove(lowercase_		)

						self.dq_store.appendleft(lowercase_		)
						self.key_reference.add(lowercase_		)







					def        __lowerCAmelCase (       self			:				int		):
						for k in self.dq_store:
							print(lowercase_		)







					def __repr__(       self			:				Tuple		):
						return F'LRUCache({self._MAX_CAPACITY}) => {list(self.dq_store		)}'


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							__UpperCamelCase  :      LRUCache[str | int]							      =		LRUCache(4)
							lru_cache.refer('''A''')
							lru_cache.refer(2)
							lru_cache.refer(3)
							lru_cache.refer('''A''')
							lru_cache.refer(4)
							lru_cache.refer(5)
							lru_cache.display()

							print(lru_cache)
							assert str(lru_cache) == "LRUCache(4) => [5, 4, 'A', 3]"




