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:
		__lowerCamelCase					:	Tuple       =  None

__lowerCamelCase					:	Union[str, Any]       =  logging.get_logger(__name__)
__lowerCamelCase					:	str       =  {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

__lowerCamelCase					:	Optional[int]       =  {
    '''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'''
        ),
    },
}

__lowerCamelCase					:	List[str]       =  {
    '''google/bigbird-roberta-base''': 40_96,
    '''google/bigbird-roberta-large''': 40_96,
    '''google/bigbird-base-trivia-itc''': 40_96,
}


__lowerCamelCase					:	Optional[Any]       =  '''▁'''






class 		a__						(					A__					):
					A	       =							VOCAB_FILES_NAMES
					A	       =							PRETRAINED_VOCAB_FILES_MAP
					A	       =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A	       =							BigBirdTokenizer
					A	       =							['input_ids', 'attention_mask']
					A	       =							[]

					def __init__(    self      :       Union[str, Any],_A      :       Any=None,_A      :       Any=None,_A      :       str="<unk>",_A      :       str="<s>",_A      :       int="</s>",_A      :       Union[str, Any]="<pad>",_A      :       Dict="[SEP]",_A      :       int="[MASK]",_A      :       int="[CLS]",**_A      :       Any,):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Dict				      =    AddedToken(_A,lstrip=_A,rstrip=_A    ) if isinstance(_A,_A    ) else bos_token
							SCREAMING_SNAKE_CASE_  :		int				      =    AddedToken(_A,lstrip=_A,rstrip=_A    ) if isinstance(_A,_A    ) else eos_token
							SCREAMING_SNAKE_CASE_  :		Dict				      =    AddedToken(_A,lstrip=_A,rstrip=_A    ) if isinstance(_A,_A    ) else unk_token
							SCREAMING_SNAKE_CASE_  :		str				      =    AddedToken(_A,lstrip=_A,rstrip=_A    ) if isinstance(_A,_A    ) else pad_token
							SCREAMING_SNAKE_CASE_  :		int				      =    AddedToken(_A,lstrip=_A,rstrip=_A    ) if isinstance(_A,_A    ) else cls_token
							SCREAMING_SNAKE_CASE_  :		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
							SCREAMING_SNAKE_CASE_  :		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,)

							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    vocab_file
							SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    False if not self.vocab_file else True

					def 				__UpperCamelCase   (    self      :       Union[str, Any],_A      :       List[int],_A      :       Optional[List[int]] = None    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    [self.sep_token_id]
							SCREAMING_SNAKE_CASE_  :		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      :       Union[str, Any],_A      :       List[int],_A      :       Optional[List[int]] = None,_A      :       bool = False    ):







							"""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      :       List[Any],_A      :       List[int],_A      :       Optional[List[int]] = None    ):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    [self.sep_token_id]
							SCREAMING_SNAKE_CASE_  :		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      :       str,_A      :       str,_A      :       Optional[str] = None    ):







							"""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
							SCREAMING_SNAKE_CASE_  :		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()
