



'''simple docstring'''





import os
from typing import List, Optional, Union

from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging


lowercase_		       =  logging.get_logger(__name__)

lowercase_		       =  {'vocab_file': 'vocab.txt'}

lowercase_		       =  {
    'vocab_file': {
        'facebook/esm2_t6_8M_UR50D': 'https://huggingface.co/facebook/esm2_t6_8M_UR50D/resolve/main/vocab.txt',
        'facebook/esm2_t12_35M_UR50D': 'https://huggingface.co/facebook/esm2_t12_35M_UR50D/resolve/main/vocab.txt',
    },
}

lowercase_		       =  {
    'facebook/esm2_t6_8M_UR50D': 1_024,
    'facebook/esm2_t12_35M_UR50D': 1_024,
}




def lowerCAmelCase  (__A):



     """simple docstring"""



     with open(a__  ,	'''r''') as f:
          _a      =  f.read().splitlines()
          return [l.strip() for l in lines]






class __A			(  A						):



 '''simple docstring'''







 __lowerCamelCase    :       Any          =       VOCAB_FILES_NAMES
 __lowerCamelCase    :       int          =       PRETRAINED_VOCAB_FILES_MAP
 __lowerCamelCase    :       Dict          =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCamelCase    :       List[str]          =       ['input_ids', 'attention_mask']



 def __init__(self ,   A ,   A="<unk>" ,   A="<cls>" ,   A="<pad>" ,   A="<mask>" ,   A="<eos>" ,   **A ,   )    ->     str:


      """simple docstring"""



      super().__init__(**_snake_case       )
      _a      =  load_vocab_file(_snake_case       )
      _a      =  dict(enumerate(self.all_tokens       )       )
      _a      =  {tok: ind for ind, tok in enumerate(self.all_tokens       )}
      _a      =  unk_token
      _a      =  cls_token
      _a      =  pad_token
      _a      =  mask_token
      _a      =  eos_token
      _a      =  self.all_tokens
      self._create_trie(self.unique_no_split_tokens       )



 def 					a__  (self ,   A       )    ->     str:


      """simple docstring"""



      return self._id_to_token.get(_snake_case ,   self.unk_token       )



 def 					a__  (self ,   A       )    ->     int:


      """simple docstring"""



      return self._token_to_id.get(_snake_case ,   self._token_to_id.get(self.unk_token       )       )



 def 					a__  (self ,   A ,   **A       )    ->     Optional[int]:


      """simple docstring"""



      return text.split()



 def 					a__  (self ,   A=False       )    ->     str:


      """simple docstring"""



      return len(self._id_to_token       )



 def 					a__  (self       )    ->     Optional[Any]:


      """simple docstring"""



      return {token: i for i, token in enumerate(self.all_tokens       )}



 def 					a__  (self ,   A       )    ->     int:


      """simple docstring"""



      return self._token_to_id.get(_snake_case ,   self._token_to_id.get(self.unk_token       )       )



 def 					a__  (self ,   A       )    ->     str:


      """simple docstring"""



      return self._id_to_token.get(_snake_case ,   self.unk_token       )



 def 					a__  (self ,   A ,   A = None       )    ->     List[int]:


      """simple docstring"""



      _a      =  [self.cls_token_id]
      _a      =  [self.eos_token_id]  # No sep token in ESM vocabulary
      if token_ids_a is None:
           if self.eos_token_id is None:
                return cls + token_ids_a
           else:
                return cls + token_ids_a + sep
      elif self.eos_token_id is None:
           raise ValueError('''Cannot tokenize multiple sequences when EOS token is not set!'''       )
      return cls + token_ids_a + sep + token_ids_a + sep  # Multiple inputs always have an EOS token



 def 					a__  (self ,   A ,   A = None ,   A = False       )    ->     List[int]:


      """simple docstring"""



      if already_has_special_tokens:
           if token_ids_a is not None:
                raise ValueError(
                    '''You should not supply a second sequence if the provided sequence of '''
                    '''ids is already formatted with special tokens for the model.'''       )

           return [1 if token in self.all_special_ids else 0 for token in token_ids_a]
      _a      =  [1] + ([0] * len(_snake_case       )) + [1]
      if token_ids_a is not None:
           mask += [0] * len(_snake_case       ) + [1]
      return mask



 def 					a__  (self ,   A ,   A       )    ->     Optional[Any]:


      """simple docstring"""



      _a      =  os.path.join(_snake_case ,   (filename_prefix + '''-''' if filename_prefix else '''''') + '''vocab.txt'''       )
      with open(_snake_case ,   '''w'''       ) as f:
           f.write('''\n'''.join(self.all_tokens       )       )
      return (vocab_file,)



 @property
 def 					a__  (self       )    ->     int:


      """simple docstring"""



      return self.get_vocab_size(with_added_tokens=_snake_case       )



 def 					a__  (self ,   A ,   A = False       )    ->     int:


      """simple docstring"""



      return super()._add_tokens(_snake_case ,   special_tokens=_snake_case       )





def     __lowerCAmelCase			(			a__						,    a__						,    a__  )       ->  list:
				__a										=    len(a__  )
				__a										=    [[0] * n for i in range(a__  )]
				for i in range(a__  ):
								__a										=    y_points[i]

				for i in range(2						,    a__  ):
								for j in range(a__						,    a__  ):
												__a										=    (
												    (xa - x_points[j - i + 1]) * q[j][i - 1]
												    - (xa - x_points[j]) * q[j - 1][i - 1]
												) / (x_points[j] - x_points[j - i + 1])

				return [q[n - 1][n - 1], q]


if __name__ == "__main__":
					import doctest

					doctest.testmod()