
'''simple docstring'''





import os
import warnings
from pathlib import Path
from typing import Optional, Union

from .dynamic_module_utils import custom_object_save
from .tokenization_utils_base import PreTrainedTokenizerBase
from .utils import PushToHubMixin, copy_func, direct_transformers_import, logging


a__						:				Union[str, Any]           =    logging.get_logger(__name__)

# Dynamically import the Transformers module to grab the attribute classes of the processor form their names.
a__						:				Optional[int]           =    direct_transformers_import(Path(__file__).parent)


a__						:				Dict           =    {
    "AutoTokenizer": "PreTrainedTokenizerBase",
    "AutoFeatureExtractor": "FeatureExtractionMixin",
    "AutoImageProcessor": "ImageProcessingMixin",
}


class 	UpperCamelCase__					(      SCREAMING_SNAKE_CASE):
 UpperCAmelCase__      :      Optional[int]  			=   ['feature_extractor', 'tokenizer']
 # Names need to be attr_class for attr in attributes
 UpperCAmelCase__      :      List[Any]  			=   None
 UpperCAmelCase__      :      Optional[Any]  			=   None
 UpperCAmelCase__      :      Optional[int]  			=   None






 def __init__(     self					:Union[str, Any]		,			*_A					:Union[str, Any]		,			**_A					:int     )			->     int:







       '''simple docstring'''



       for key in kwargs:
             if key not in self.attributes:
                   raise TypeError(F'Unexpected keyword argument {key}.'     )
       for arg, attribute_name in zip(_A		,			self.attributes     ):
             if attribute_name in kwargs:
                   raise TypeError(F'Got multiple values for argument {attribute_name}.'     )
             else:
                   __A    		=     arg

       if len(_A     ) != len(self.attributes     ):
             raise ValueError(
                 F'This processor requires {len(self.attributes     )} arguments: {", ".join(self.attributes     )}. Got '
                 F'{len(_A     )} arguments instead.'     )

       # Check each arg is of the proper class (this will also catch a user initializing in the wrong order)
       for attribute_name, arg in kwargs.items():
             __A    		=     getattr(self		,			F'{attribute_name}_class'     )
             # Nothing is ever going to be an instance of "AutoXxx", in that case we check the base class.
             __A    		=     AUTO_TO_BASE_CLASS_MAPPING.get(_A		,			_A     )
             if isinstance(_A		,			_A     ):
                   __A    		=     tuple(getattr(_A		,			_A     ) for n in class_name if n is not None     )
             else:
                   __A    		=     getattr(_A		,			_A     )

             if not isinstance(_A		,			_A     ):
                   raise ValueError(
                       F'Received a {type(_A     ).__name__} for argument {attribute_name}, but a {class_name} was expected.'     )

             setattr(self		,			_A		,			_A     )






 def __repr__(     self					:List[Any]     )			->     int:







       '''simple docstring'''



       __A    		=     [F'- {name}: {repr(getattr(self		,			_A     )     )}' for name in self.attributes]
       __A    		=     '\n'.join(_A     )
       return F'{self.__class__.__name__}:\n{attributes_repr}'






 def 		lowercase_  (     self					:List[str]		,			_A					:List[Any]		,			_A					:bool = False		,			**_A					:Union[str, Any]     )			->     List[str]:







       '''simple docstring'''



       os.makedirs(_A		,			exist_ok=_A     )

       if push_to_hub:
             __A    		=     kwargs.pop('commit_message'		,			_A     )
             __A    		=     kwargs.pop('repo_id'		,			save_directory.split(os.path.sep     )[-1]     )
             __A    		=     self._create_repo(_A		,			**_A     )
             __A    		=     self._get_files_timestamps(_A     )
       # If we have a custom config, we copy the file defining it in the folder and set the attributes so it can be
       # loaded from the Hub.
       if self._auto_class is not None:
             __A    		=     [getattr(self		,			_A     ) for attribute_name in self.attributes]
             __A    		=     [(a.init_kwargs if isinstance(_A		,			_A     ) else a) for a in attrs]
             custom_object_save(self		,			_A		,			config=_A     )

       for attribute_name in self.attributes:
             __A    		=     getattr(self		,			_A     )
             # Include the processor class in the attribute config so this processor can then be reloaded with the
             # `AutoProcessor` API.
             if hasattr(_A		,			'_set_processor_class'     ):
                   attribute._set_processor_class(self.__class__.__name__     )
             attribute.save_pretrained(_A     )

       if self._auto_class is not None:
             # We added an attribute to the init_kwargs of the tokenizers, which needs to be cleaned up.
             for attribute_name in self.attributes:
                   __A    		=     getattr(self		,			_A     )
                   if isinstance(_A		,			_A     ):
                         del attribute.init_kwargs["auto_map"]

       if push_to_hub:
             self._upload_modified_files(
                 _A		,			_A		,			_A		,			commit_message=_A		,			token=kwargs.get('use_auth_token'     )		,			)






 @classmethod
 def 		lowercase_  (     cls					:str		,			_A					:Union[str, os.PathLike]		,			_A					:Optional[Union[str, os.PathLike]] = None		,			_A					:bool = False		,			_A					:bool = False		,			_A					:Optional[Union[str, bool]] = None		,			_A					:str = "main"		,			**_A					:Optional[Any]		,			)			->     Dict:







       '''simple docstring'''



       __A    		=     cache_dir
       __A    		=     force_download
       __A    		=     local_files_only
       __A    		=     revision

       __A    		=     kwargs.pop('use_auth_token'		,			_A     )
       if use_auth_token is not None:
             warnings.warn(
                 'The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers.'		,			_A     )
             if token is not None:
                   raise ValueError(
                       '`token` and `use_auth_token` are both specified. Please set only the argument `token`.'     )
             __A    		=     use_auth_token

       if token is not None:
             # change to `token` in a follow-up PR
             __A    		=     token

       __A    		=     cls._get_arguments_from_pretrained(_A		,			**_A     )
       return cls(*_A     )






 @classmethod
 def 		lowercase_  (     cls					:Union[str, Any]		,			_A					:Union[str, Any]="AutoProcessor"     )			->     List[Any]:







       '''simple docstring'''



       if not isinstance(_A		,			_A     ):
             __A    		=     auto_class.__name__

       import transformers.models.auto as auto_module

       if not hasattr(_A		,			_A     ):
             raise ValueError(F'{auto_class} is not a valid auto class.'     )

       __A    		=     auto_class






 @classmethod
 def 		lowercase_  (     cls					:List[Any]		,			_A					:Tuple		,			**_A					:Tuple     )			->     Optional[Any]:







       '''simple docstring'''



       __A    		=     []
       for attribute_name in cls.attributes:
             __A    		=     getattr(cls		,			F'{attribute_name}_class'     )
             if isinstance(_A		,			_A     ):
                   __A    		=     tuple(getattr(_A		,			_A     ) if n is not None else None for n in class_name     )
                   __A    		=     kwargs.get('use_fast'		,			_A     )
                   if use_fast and classes[1] is not None:
                         __A    		=     classes[1]
                   else:
                         __A    		=     classes[0]
             else:
                   __A    		=     getattr(_A		,			_A     )

             args.append(attribute_class.from_pretrained(_A		,			**_A     )     )
       return args






 @property
 def 		lowercase_  (     self					:Optional[Any]     )			->     int:







       '''simple docstring'''



       __A    		=     getattr(self		,			self.attributes[0]     )
       return getattr(_A		,			'model_input_names'		,			_A     )
a__						:				int           =    copy_func(ProcessorMixin.push_to_hub)
if ProcessorMixin.push_to_hub.__doc__ is not None:
 a__						:				Tuple           =    ProcessorMixin.push_to_hub.__doc__.format(
     object="processor", object_class="AutoProcessor", object_files="processor files"
 )








'''simple docstring'''





import itertools
from pathlib import Path





def     snake_case							(						UpperCAmelCase		)->     int:







      """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     snake_case							(						UpperCAmelCase = "keylog.txt"		)->     int:







      """simple docstring"""
      __A    		=     Path(UpperCAmelCase		).parent.joinpath(UpperCAmelCase		).read_text().splitlines()

      return find_secret_passcode(UpperCAmelCase		)


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






