



'''simple docstring'''






import numpy as np

lowerCAmelCase: Optional[Any]							=						[
    ['a', 'b', 'c', 'd', 'e'],
    ['f', 'g', 'h', 'i', 'k'],
    ['l', 'm', 'n', 'o', 'p'],
    ['q', 'r', 's', 't', 'u'],
    ['v', 'w', 'x', 'y', 'z'],
]

class 							a__:







    def __init__(				self			:  Any     ):
      a						: int					       =					np.array(__snake_case     )







    def       lowercase_	(				self			:  Union[str, Any]						,      __snake_case			:  str     ):
      a       ,     a						: Tuple					       =					np.where(letter == self.SQUARE     )
      a						: Dict					       =					np.concatenate([indexa + 1, indexa + 1]     )
      return indexes







    def       lowercase_	(				self			:  Any						,      __snake_case			:  int						,      __snake_case			:  int     ):
      a						: Optional[Any]					       =					self.SQUARE[indexa - 1, indexa - 1]
      return letter







    def       lowercase_	(				self			:  Optional[Any]						,      __snake_case			:  str     ):
      a						: Optional[int]					       =					message.lower()
      a						: List[Any]					       =					message.replace(' '						,      ''     )
      a						: Optional[int]					       =					message.replace('j'						,      'i'     )

      a						: List[str]					       =					np.empty((2, len(__snake_case     ))     )
      for letter_index in range(len(__snake_case     )     ):
        a						: Optional[int]					       =					self.letter_to_numbers(message[letter_index]     )

        a						: Union[str, Any]					       =					numbers[0]
        a						: Dict					       =					numbers[1]

      a						: Any					       =					first_step.reshape(2 * len(__snake_case     )     )
      a						: Dict					       =					''
      for numbers_index in range(len(__snake_case     )     ):
        a						: Tuple					       =					int(second_step[numbers_index * 2]     )
        a						: List[str]					       =					int(second_step[(numbers_index * 2) + 1]     )
        a						: Any					       =					self.numbers_to_letter(__snake_case						,      __snake_case     )
        a						: str					       =					encoded_message + letter

      return encoded_message







    def       lowercase_	(				self			:  Any						,      __snake_case			:  str     ):
      a						: List[Any]					       =					message.lower()
      message.replace(' '						,      ''     )
      a						: Union[str, Any]					       =					np.empty(2 * len(__snake_case     )     )
      for letter_index in range(len(__snake_case     )     ):
        a						: int					       =					self.letter_to_numbers(message[letter_index]     )
        a						: List[Any]					       =					numbers[0]
        a						: str					       =					numbers[1]

      a						: List[str]					       =					first_step.reshape((2, len(__snake_case     ))     )
      a						: Tuple					       =					''
      for numbers_index in range(len(__snake_case     )     ):
        a						: List[Any]					       =					int(second_step[0, numbers_index]     )
        a						: Optional[Any]					       =					int(second_step[1, numbers_index]     )
        a						: Union[str, Any]					       =					self.numbers_to_letter(__snake_case						,      __snake_case     )
        a						: Dict					       =					decoded_message + letter

      return decoded_message




'''simple docstring'''






import torch

from transformers import AutoModel

class 							a__( torch.nn.Module     ):







    def __init__(				self			:  Any						,      __snake_case			:  str="sayef/fsner-bert-base-uncased"     ):
      super(__snake_case						,      self     ).__init__()

      a						: List[str]					       =					AutoModel.from_pretrained(__snake_case						,      return_dict=__snake_case     )
      a						: Optional[Any]					       =					torch.nn.CosineSimilarity(3						,      1e-0_8     )
      a						: Tuple					       =					torch.nn.Softmax(dim=1     )







    def       lowercase_	(				self			:  List[str]						,      **__snake_case			:  int     ):
      return self.bert(**__snake_case     ).last_hidden_state







    def       lowercase_	(				self			:  Optional[int]						,      __snake_case			:  Union[str, Any]     ):
      return token_embeddings.sum(2						,      keepdim=__snake_case     )







    def       lowercase_	(				self			:  str						,      __snake_case			:  Tuple						,      __snake_case			:  List[Any]						,      __snake_case			:  Optional[Any]=1     ):
      return self.softmax(T * self.cos(__snake_case						,      __snake_case     )     )







    def       lowercase_	(				self			:  int						,      __snake_case			:  int						,      __snake_case			:  Tuple     ):
      a						: List[Any]					       =					W_supports['sizes'].tolist()
      a						: Any					       =					W_supports['start_token_id'].item()
      a						: int					       =					W_supports['end_token_id'].item()

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

      a						: Optional[Any]					       =					self.BERT(**__snake_case     )
      a						: Tuple					       =					self.BERT(**__snake_case     )

      a						: Dict					       =					None
      a						: Optional[Any]					       =					None

      a						: Union[str, Any]					       =					W_supports['input_ids'] == start_token_id
      a						: str					       =					W_supports['input_ids'] == end_token_id

      for i, size in enumerate(__snake_case     ):
        if i == 0:
          a						: Optional[int]					       =					0
        else:
          a						: Tuple					       =					support_sizes[i - 1]

        a						: Tuple					       =					S[s : s + size][start_token_masks[s : s + size]]
        a						: int					       =					S[s : s + size][end_token_masks[s : s + size]]

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

        if p_starts is not None:
          a						: List[Any]					       =					torch.vstack((p_starts, p_start)     )
          a						: List[Any]					       =					torch.vstack((p_ends, p_end)     )
        else:
          a						: List[Any]					       =					p_start
          a						: Optional[int]					       =					p_end

      return p_starts, p_ends