






"""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_xlm_roberta import XLMRobertaTokenizer
else:
       lowercase_    					=					None


lowercase_    					=					logging.get_logger(__name__)

lowercase_    					=					{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

lowercase_    					=					{
    'vocab_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json'
        ),
    },
}

lowercase_    					=					{
    'xlm-roberta-base': 512,
    'xlm-roberta-large': 512,
    'xlm-roberta-large-finetuned-conll02-dutch': 512,
    'xlm-roberta-large-finetuned-conll02-spanish': 512,
    'xlm-roberta-large-finetuned-conll03-english': 512,
    'xlm-roberta-large-finetuned-conll03-german': 512,
}


class  snake_case		(							_lowerCAmelCase						):


   '''simple docstring'''

   A_						:     str									=			VOCAB_FILES_NAMES
   A_						:     List[str]									=			PRETRAINED_VOCAB_FILES_MAP
   A_						:     Any									=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A_						:     Optional[Any]									=			['input_ids', 'attention_mask']
   A_						:     Optional[int]									=			XLMRobertaTokenizer


   def __init__(     self			:					int,	_lowerCamelCase			:					Dict=None,	_lowerCamelCase			:					Any=None,	_lowerCamelCase			:					Optional[int]="<s>",	_lowerCamelCase			:					Union[str, Any]="</s>",	_lowerCamelCase			:					List[Any]="</s>",	_lowerCamelCase			:					Union[str, Any]="<s>",	_lowerCamelCase			:					Dict="<unk>",	_lowerCamelCase			:					Optional[int]="<pad>",	_lowerCamelCase			:					Dict="<mask>",	**_lowerCamelCase			:					Tuple,	):

     '''simple docstring'''
     __A						      =			AddedToken(_lowerCamelCase,	lstrip=_lowerCamelCase,	rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,	_lowerCamelCase  ) else mask_token

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

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


   def     _SCREAMING_SNAKE_CASE    (     self			:					Dict,	_lowerCamelCase			:					List[int],	_lowerCamelCase			:					Optional[List[int]] = None  ):

     '''simple docstring'''






     if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
     __A						      =			[self.cls_token_id]
     __A						      =			[self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep


   def     _SCREAMING_SNAKE_CASE    (     self			:					List[str],	_lowerCamelCase			:					List[int],	_lowerCamelCase			:					Optional[List[int]] = None  ):

     '''simple docstring'''
     __A						      =			[self.sep_token_id]
     __A						      =			[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 + sep + token_ids_a + sep  ) * [0]






   def     _SCREAMING_SNAKE_CASE    (     self			:					Optional[int],	_lowerCamelCase			:					str,	_lowerCamelCase			:					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(_lowerCamelCase  ):
       logger.error(f'Vocabulary path ({save_directory}) should be a directory.'  )
       return
     __A						      =			os.path.join(
         _lowerCamelCase,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

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

     return (out_vocab_file,)












"""simple docstring"""


import itertools
from pathlib import Path



def  lowerCAmelCase    (   __UpperCamelCase			):




  """simple docstring"""







  __A						      =			[tuple(__UpperCamelCase			) for login in logins]

  __A						      =			{char for login in split_logins for char in login}

  for permutation in itertools.permutations(__UpperCamelCase			):
    __A						      =			True
    for login in logins:
      if not (
          permutation.index(login[0]			)
          < permutation.index(login[1]			)
          < permutation.index(login[2]			)
      ):
        __A						      =			False
        break

    if satisfied:
      return int(''''''.join(__UpperCamelCase			)			)

  raise Exception('''Unable to find the secret passcode'''			)



def  lowerCAmelCase    (   __UpperCamelCase = "keylog.txt"			):




  """simple docstring"""







  __A						      =			Path(__UpperCamelCase			).parent.joinpath(__UpperCamelCase			).read_text().splitlines()

  return find_secret_passcode(__UpperCamelCase			)


if __name__ == "__main__":
       print(F'''{solution() = }''')




