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:
     __snake_case						=			None

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

__snake_case						=			{
    '''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'''
        ),
    },
}

__snake_case						=			{
    '''google/bigbird-roberta-base''': 40_96,
    '''google/bigbird-roberta-large''': 40_96,
    '''google/bigbird-base-trivia-itc''': 40_96,
}


__snake_case						=			'''▁'''







class 	__snake_case      (   A__      ):
 __lowerCamelCase			:      Tuple           =					VOCAB_FILES_NAMES
 __lowerCamelCase			:      List[str]           =					PRETRAINED_VOCAB_FILES_MAP
 __lowerCamelCase			:      Optional[Any]           =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCamelCase			:      Optional[int]           =					BigBirdTokenizer
 __lowerCamelCase			:      List[Any]           =					["""input_ids""", """attention_mask"""]
 __lowerCamelCase			:      Union[str, Any]           =					[]
 def __init__(     self						,      snake_case__=None						,      snake_case__=None						,      snake_case__="<unk>"						,      snake_case__="<s>"						,      snake_case__="</s>"						,      snake_case__="<pad>"						,      snake_case__="[SEP]"						,      snake_case__="[MASK]"						,      snake_case__="[CLS]"						,      **snake_case__						,      )		->							Dict:
       '''simple docstring'''





       UpperCAmelCase			:       Dict			     =AddedToken(_A						,      lstrip=_A						,      rstrip=_A  ) if isinstance(_A						,      _A  ) else bos_token
       UpperCAmelCase			:       int			     =AddedToken(_A						,      lstrip=_A						,      rstrip=_A  ) if isinstance(_A						,      _A  ) else eos_token
       UpperCAmelCase			:       Dict			     =AddedToken(_A						,      lstrip=_A						,      rstrip=_A  ) if isinstance(_A						,      _A  ) else unk_token
       UpperCAmelCase			:       str			     =AddedToken(_A						,      lstrip=_A						,      rstrip=_A  ) if isinstance(_A						,      _A  ) else pad_token
       UpperCAmelCase			:       int			     =AddedToken(_A						,      lstrip=_A						,      rstrip=_A  ) if isinstance(_A						,      _A  ) else cls_token
       UpperCAmelCase			:       List[str]			     =AddedToken(_A						,      lstrip=_A						,      rstrip=_A  ) if isinstance(_A						,      _A  ) else sep_token

       # Mask token behave like a normal word, i.e. include the space before it
       UpperCAmelCase			:       List[Any]			     =AddedToken(_A						,      lstrip=_A						,      rstrip=_A  ) if isinstance(_A						,      _A  ) else mask_token

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

       UpperCAmelCase			:       Optional[int]			     =vocab_file
       UpperCAmelCase			:       Union[str, Any]			     =False if not self.vocab_file else True
 def 		UpperCAmelCase__				(     self						,      snake_case__						,      snake_case__ = None  )		->							int:
       '''simple docstring'''





       UpperCAmelCase			:       List[Any]			     =[self.sep_token_id]
       UpperCAmelCase			:       Optional[int]			     =[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 		UpperCAmelCase__				(     self						,      snake_case__						,      snake_case__ = None						,      snake_case__ = False  )		->							str:
       '''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 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(_A  )) + [1]
       return [1] + ([0] * len(_A  )) + [1] + ([0] * len(_A  )) + [1]
 def 		UpperCAmelCase__				(     self						,      snake_case__						,      snake_case__ = None  )		->							Dict:
       '''simple docstring'''





       UpperCAmelCase			:       Optional[int]			     =[self.sep_token_id]
       UpperCAmelCase			:       List[str]			     =[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 		UpperCAmelCase__				(     self						,      snake_case__						,      snake_case__ = None  )		->							List[str]:
       '''simple docstring'''





       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(_A  ):
             logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
             return
       UpperCAmelCase			:       List[str]			     =os.path.join(
           _A						,      (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

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

       return (out_vocab_file,)

from functools import lru_cache




@lru_cache
def       _snake_case	(   lowerCAmelCase							:   int	):
		"""simple docstring"""







		if num < 0:
				raise ValueError("Number should not be negative."	)

		return 1 if num in (0, 1) else num * factorial(num - 1	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
