






"""simple docstring"""







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_	:    int            =      None

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

lowerCAmelCase_	:    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_	:    Union[str, Any]            =      {
    '''google/bigbird-roberta-base''': 4_0_9_6,
    '''google/bigbird-roberta-large''': 4_0_9_6,
    '''google/bigbird-base-trivia-itc''': 4_0_9_6,
}


lowerCAmelCase_	:    int            =      '''▁'''





class   UpperCamelCase_ (       a_  ):
  _A       :					List[Any]				=	VOCAB_FILES_NAMES
  _A       :					Optional[Any]				=	PRETRAINED_VOCAB_FILES_MAP
  _A       :					Any				=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _A       :					Any				=	BigBirdTokenizer
  _A       :					Union[str, Any]				=	['input_ids', 'attention_mask']
  _A       :					List[int]				=	[]



  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__ ,		)			->			Union[str, Any]:



         """simple docstring"""





         UpperCAmelCase	    =			AddedToken(snake_case__ ,		lstrip=snake_case__ ,		rstrip=snake_case__				) if isinstance(snake_case__ ,		snake_case__				) else bos_token
         UpperCAmelCase	    =			AddedToken(snake_case__ ,		lstrip=snake_case__ ,		rstrip=snake_case__				) if isinstance(snake_case__ ,		snake_case__				) else eos_token
         UpperCAmelCase	    =			AddedToken(snake_case__ ,		lstrip=snake_case__ ,		rstrip=snake_case__				) if isinstance(snake_case__ ,		snake_case__				) else unk_token
         UpperCAmelCase	    =			AddedToken(snake_case__ ,		lstrip=snake_case__ ,		rstrip=snake_case__				) if isinstance(snake_case__ ,		snake_case__				) else pad_token
         UpperCAmelCase	    =			AddedToken(snake_case__ ,		lstrip=snake_case__ ,		rstrip=snake_case__				) if isinstance(snake_case__ ,		snake_case__				) else cls_token
         UpperCAmelCase	    =			AddedToken(snake_case__ ,		lstrip=snake_case__ ,		rstrip=snake_case__				) if isinstance(snake_case__ ,		snake_case__				) else sep_token

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

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

         UpperCAmelCase	    =			vocab_file
         UpperCAmelCase	    =			False if not self.vocab_file else True



  def 		UpperCamelCase_				(      self ,		snake_case__ ,		snake_case__ = None				)			->			List[int]:



         """simple docstring"""





         UpperCAmelCase	    =			[self.sep_token_id]
         UpperCAmelCase	    =			[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				)			->			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 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(snake_case__				)) + [1]
         return [1] + ([0] * len(snake_case__				)) + [1] + ([0] * len(snake_case__				)) + [1]



  def 		UpperCamelCase_				(      self ,		snake_case__ ,		snake_case__ = None				)			->			List[int]:



         """simple docstring"""





         UpperCAmelCase	    =			[self.sep_token_id]
         UpperCAmelCase	    =			[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				)			->			Tuple[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(snake_case__				):
                logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''				)
                return
         UpperCAmelCase	    =			os.path.join(
             snake_case__ ,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

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

         return (out_vocab_file,)








"""simple docstring"""







import random
from typing import Any






def       _lowerCAmelCase       (      lowerCAmelCase		):







       '''simple docstring'''
       for _ in range(len(lowerCAmelCase		)		):
              UpperCAmelCase	    =			random.randint(0	,      len(lowerCAmelCase		) - 1		)
              UpperCAmelCase	    =			random.randint(0	,      len(lowerCAmelCase		) - 1		)
              UpperCAmelCase    ,       UpperCAmelCase	    =			data[b], data[a]
       return data


if __name__ == "__main__":
 lowerCAmelCase_	:    Tuple            =      [0, 1, 2, 3, 4, 5, 6, 7]
 lowerCAmelCase_	:    List[str]            =      ['''python''', '''says''', '''hello''', '''!''']
 print('''Fisher-Yates Shuffle:''')
 print('''List''', integers, strings)
 print('''FY Shuffle''', fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))
