

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

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


if is_sentencepiece_available():
     from .tokenization_reformer import ReformerTokenizer
else:
     _lowerCamelCase       :     Union[str, Any]           =							None


_lowerCamelCase       :     Any           =							logging.get_logger(__name__)


_lowerCamelCase       :     Dict           =							"▁"

_lowerCamelCase       :     int           =							{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

_lowerCamelCase       :     int           =							{
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    },
    "tokenizer_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json"
        )
    },
}

_lowerCamelCase       :     str           =							{
    "google/reformer-crime-and-punishment": 5_2_4_2_8_8,
}





class       __UpperCAmelCase  ( lowerCamelCase__		):
   UpperCamelCase       =  VOCAB_FILES_NAMES
   UpperCamelCase       =  PRETRAINED_VOCAB_FILES_MAP
   UpperCamelCase       =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   UpperCamelCase       =  ["""input_ids""", """attention_mask"""]
   UpperCamelCase       =  ReformerTokenizer



   def __init__(							self							:  List[Any],	__A							:  Optional[Any]=None,	__A							:  List[Any]=None,	__A							:  Dict="</s>",	__A							:  List[Any]="<unk>",	__A							:  Any=[],	**__A							:  Any,	):
     super().__init__(
         __A,	tokenizer_file=__A,	eos_token=__A,	unk_token=__A,	additional_special_tokens=__A,	**__A,	)

     UpperCAmelCase :							List[Any]								=				vocab_file
     UpperCAmelCase :							List[Any]								=				False if not self.vocab_file else True





   def  __magic_name__					(							self							:  str,	__A							:  str,	__A							:  Optional[str] = None		):
     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,)








import decimal

def     a__  (	)						->		int:
  UpperCAmelCase :							List[Any]								=				0
  UpperCAmelCase :							Dict								=				decimal.Context(prec=105    )
  for i in range(2       ,				100    ):
    UpperCAmelCase :							List[str]								=				decimal.Decimal(UpperCAmelCase    )
    UpperCAmelCase :							List[str]								=				number.sqrt(UpperCAmelCase    )
    if len(str(UpperCAmelCase    )    ) > 1:
      answer += int(str(UpperCAmelCase    )[0]    )
      UpperCAmelCase :							str								=				str(UpperCAmelCase    )[2:101]
      answer += sum(int(UpperCAmelCase    ) for x in sqrt_number_str    )
  return answer


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(f"""{solution() = }""")





