


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

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


if is_sentencepiece_available():
					from .tokenization_deberta_va import DebertaVaTokenizer
else:
					UpperCamelCase			:					int         =							None

UpperCamelCase			:					List[str]         =							logging.get_logger(__name__)

UpperCamelCase			:					List[str]         =							{'''vocab_file''': '''spm.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCamelCase			:					int         =							{
    '''vocab_file''': {
        '''microsoft/deberta-v2-xlarge''': '''https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xxlarge''': '''https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'''
        ),
        '''microsoft/deberta-v2-xxlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'''
        ),
    }
}

UpperCamelCase			:					List[str]         =							{
    '''microsoft/deberta-v2-xlarge''': 512,
    '''microsoft/deberta-v2-xxlarge''': 512,
    '''microsoft/deberta-v2-xlarge-mnli''': 512,
    '''microsoft/deberta-v2-xxlarge-mnli''': 512,
}

UpperCamelCase			:					int         =							{
    '''microsoft/deberta-v2-xlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xlarge-mnli''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge-mnli''': {'''do_lower_case''': False},
}

class      __snake_case				(   _lowercase):
					SCREAMING_SNAKE_CASE_		:       Union[str, Any]								=			VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE_		:       List[str]								=			PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE_		:       str								=			PRETRAINED_INIT_CONFIGURATION
					SCREAMING_SNAKE_CASE_		:       Any								=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE_		:       Tuple								=			DebertaVaTokenizer
					def __init__(						self       :						Tuple	,      _lowerCAmelCase       :						Dict=None	,      _lowerCAmelCase       :						List[str]=None	,      _lowerCAmelCase       :						int=False	,      _lowerCAmelCase       :						List[str]=False	,      _lowerCAmelCase       :						List[Any]="[CLS]"	,      _lowerCAmelCase       :						Dict="[SEP]"	,      _lowerCAmelCase       :						Union[str, Any]="[UNK]"	,      _lowerCAmelCase       :						List[str]="[SEP]"	,      _lowerCAmelCase       :						List[Any]="[PAD]"	,      _lowerCAmelCase       :						int="[CLS]"	,      _lowerCAmelCase       :						Union[str, Any]="[MASK]"	,      **_lowerCAmelCase       :						Tuple	,      )							->					None:



											'''simple docstring'''





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

											__magic_name__					=      do_lower_case
											__magic_name__					=      split_by_punct
											__magic_name__					=      vocab_file
											__magic_name__					=      False if not self.vocab_file else True
					def 	a			(						self       :						List[str]	,      _lowerCAmelCase       :						Dict	,      _lowerCAmelCase       :						Optional[int]=None  )							->					Union[str, Any]:



											'''simple docstring'''





											if token_ids_a is None:
																	return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
											__magic_name__					=      [self.cls_token_id]
											__magic_name__					=      [self.sep_token_id]
											return cls + token_ids_a + sep + token_ids_a + sep
					def 	a			(						self       :						str	,      _lowerCAmelCase       :						Any	,      _lowerCAmelCase       :						str=None	,      _lowerCAmelCase       :						List[Any]=False  )							->					Optional[Any]:



											'''simple docstring'''





											if already_has_special_tokens:
																	return super().get_special_tokens_mask(
																	    token_ids_a=__lowerCAmelCase	,      token_ids_a=__lowerCAmelCase	,      already_has_special_tokens=__lowerCAmelCase  )

											if token_ids_a is not None:
																	return [1] + ([0] * len(__lowerCAmelCase  )) + [1] + ([0] * len(__lowerCAmelCase  )) + [1]
											return [1] + ([0] * len(__lowerCAmelCase  )) + [1]
					def 	a			(						self       :						Tuple	,      _lowerCAmelCase       :						Tuple	,      _lowerCAmelCase       :						Optional[int]=None  )							->					str:



											'''simple docstring'''





											__magic_name__					=      [self.sep_token_id]
											__magic_name__					=      [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 	a			(						self       :						Optional[int]	,      _lowerCAmelCase       :						int	,      _lowerCAmelCase       :						Optional[Any] = 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(__lowerCAmelCase  ):
																	logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
																	return
											__magic_name__					=      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,)








import itertools
from pathlib import Path

def      a    (   _lowercase :  list[str]							)  ->int:
		UpperCamelCase__								=						[tuple(_lowercase							) for login in logins]

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

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

				if satisfied:
						return int("""""".join(_lowercase							)							)

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

def      a    (   _lowercase :  str = "keylog.txt"							)  ->int:
		UpperCamelCase__								=						Path(_lowercase							).parent.joinpath(_lowercase							).read_text().splitlines()

		return find_secret_passcode(_lowercase							)


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





