



import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
    from .tokenization_big_bird import BigBirdTokenizer
else:
    __UpperCAmelCase			  =			None

__UpperCAmelCase			  =			logging.get_logger(__name__)
__UpperCAmelCase			  =			{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

__UpperCAmelCase			  =			{
    '''vocab_file''': {
        '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model''',
        '''google/bigbird-roberta-large''': (
            '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'''
        ),
        '''google/bigbird-base-trivia-itc''': (
            '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'''
        ),
    },
    '''tokenizer_file''': {
        '''google/bigbird-roberta-base''': (
            '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json'''
        ),
        '''google/bigbird-roberta-large''': (
            '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json'''
        ),
        '''google/bigbird-base-trivia-itc''': (
            '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json'''
        ),
    },
}

__UpperCAmelCase			  =			{
    '''google/bigbird-roberta-base''': 4_096,
    '''google/bigbird-roberta-large''': 4_096,
    '''google/bigbird-base-trivia-itc''': 4_096,
}


__UpperCAmelCase			  =			'''▁'''



class 							lowerCAmelCase_						(    a__				):
       UpperCAmelCase__							:   Tuple  	=    VOCAB_FILES_NAMES
       UpperCAmelCase__							:   str  	=    PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase__							:   Optional[Any]  	=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCAmelCase__							:   str  	=    BigBirdTokenizer
       UpperCAmelCase__							:   Dict  	=    ["input_ids", "attention_mask"]
       UpperCAmelCase__							:   List[int]  	=    []
       def __init__(     self,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_="<unk>",     SCREAMING_SNAKE_CASE_="<s>",     SCREAMING_SNAKE_CASE_="</s>",     SCREAMING_SNAKE_CASE_="<pad>",     SCREAMING_SNAKE_CASE_="[SEP]",     SCREAMING_SNAKE_CASE_="[MASK]",     SCREAMING_SNAKE_CASE_="[CLS]",     **SCREAMING_SNAKE_CASE_,     )	->						Optional[Any]:
          UpperCamelCase       :    Union[str, Any]		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else bos_token
          UpperCamelCase       :    Optional[Any]		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else eos_token
          UpperCamelCase       :    Tuple		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else unk_token
          UpperCamelCase       :    List[str]		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else pad_token
          UpperCamelCase       :    List[str]		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else cls_token
          UpperCamelCase       :    Optional[int]		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else sep_token

          # Mask token behave like a normal word, i.e. include the space before it
          UpperCamelCase       :    Dict		      =      AddedToken(SCREAMING_SNAKE_CASE_,     lstrip=SCREAMING_SNAKE_CASE_,     rstrip=SCREAMING_SNAKE_CASE_			) if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			) else mask_token

          super().__init__(
              SCREAMING_SNAKE_CASE_,     tokenizer_file=SCREAMING_SNAKE_CASE_,     bos_token=SCREAMING_SNAKE_CASE_,     eos_token=SCREAMING_SNAKE_CASE_,     unk_token=SCREAMING_SNAKE_CASE_,     sep_token=SCREAMING_SNAKE_CASE_,     pad_token=SCREAMING_SNAKE_CASE_,     cls_token=SCREAMING_SNAKE_CASE_,     mask_token=SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_,     )

          UpperCamelCase       :    str		      =      vocab_file
          UpperCamelCase       :    Union[str, Any]		      =      False if not self.vocab_file else True
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = None			)	->						List[int]:
          UpperCamelCase       :    List[Any]		      =      [self.sep_token_id]
          UpperCamelCase       :    Tuple		      =      [self.cls_token_id]
          if token_ids_a is None:
             return cls + token_ids_a + sep
          return cls + token_ids_a + sep + token_ids_a + sep
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = None,     SCREAMING_SNAKE_CASE_ = False			)	->						List[int]:

          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 x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

          if token_ids_a is None:
             return [1] + ([0] * len(SCREAMING_SNAKE_CASE_			)) + [1]
          return [1] + ([0] * len(SCREAMING_SNAKE_CASE_			)) + [1] + ([0] * len(SCREAMING_SNAKE_CASE_			)) + [1]
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = None			)	->						List[int]:
          UpperCamelCase       :    Optional[int]		      =      [self.sep_token_id]
          UpperCamelCase       :    Dict		      =      [self.cls_token_id]

          if token_ids_a is None:
             return len(cls + token_ids_a + sep			) * [0]
          return len(cls + token_ids_a + sep			) * [0] + len(token_ids_a + sep			) * [1]






       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_ = None			)	->						Tuple[str]:
          if not self.can_save_slow_tokenizer:
             raise ValueError(
                 'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                 'tokenizer.'			)

          if not os.path.isdir(SCREAMING_SNAKE_CASE_			):
             logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""			)
             return
          UpperCamelCase       :    Dict		      =      os.path.join(
              SCREAMING_SNAKE_CASE_,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']			)

          if os.path.abspath(self.vocab_file			) != os.path.abspath(SCREAMING_SNAKE_CASE_			):
             copyfile(self.vocab_file,     SCREAMING_SNAKE_CASE_			)

          return (out_vocab_file,)









"""simple docstring"""






import re







def 	_snake_case     (							lowercase__						):

				if len(re.findall('[ATCG]'				,       lowercase__						)						) != len(lowercase__						):
								raise ValueError('Invalid Strand'						)

				return dna.translate(dna.maketrans('ATCG'				,       'TAGC'						)						)


if __name__ == "__main__":
			import doctest

			doctest.testmod()