
from __future__ import annotations

import random
import string


class 		__magic_name__   :





  def __init__(							self    :	Any						,  lowerCamelCase__    :	str | None = None				):
       lowerCAmelCase		:					int  	=     passcode or self.__passcode_creator()
       lowerCAmelCase		:					List[str]  	=     self.__make_key_list()
       lowerCAmelCase		:					Optional[int]  	=     self.__make_shift_key()





  def __str__(							self    :	Union[str, Any]				):
       return "".join(self.__passcode				)





  def       _A							(							self    :	Tuple						,  lowerCamelCase__    :	list[int]				):
       for i in range(1						,  len(lowerCamelCase__				)						,  2				):
            iterlist[i] *= -1
       return iterlist





  def       _A							(							self    :	List[Any]				):
       lowerCAmelCase		:					Union[str, Any]  	=     string.ascii_letters + string.digits
       lowerCAmelCase		:					Optional[Any]  	=     [random.choice(lowerCamelCase__				) for _ in range(random.randint(1_0						,  2_0				)				)]
       return password





  def       _A							(							self    :	Any				):
       lowerCAmelCase		:					str  	=     (
           string.ascii_letters + string.digits + string.punctuation + ''' \t\n'''
       )

       lowerCAmelCase		:					Optional[Any]  	=     []

       # creates points known as breakpoints to break the key_list_options at those
       # points and pivot each substring
       lowerCAmelCase		:					Tuple  	=     sorted(set(self.__passcode				)				)
       lowerCAmelCase		:					list[str]  	=     []

       # algorithm for creating a new shuffled list, keys_l, out of key_list_options
       for i in key_list_options:
            temp_list.extend(lowerCamelCase__				)

            # checking breakpoints at which to pivot temporary sublist and add it into
            # keys_l
            if i in breakpoints or i == key_list_options[-1]:
                 keys_l.extend(temp_list[::-1]				)
                 temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
       return keys_l





  def       _A							(							self    :	List[Any]				):
       lowerCAmelCase		:					str  	=     sum(self.__neg_pos([ord(lowerCamelCase__				) for x in self.__passcode]				)				)
       return num if num > 0 else len(self.__passcode				)





  def       _A							(							self    :	Optional[int]						,  lowerCamelCase__    :	str				):
       lowerCAmelCase		:					Tuple  	=     ''''''

       # decoding shift like Caesar cipher algorithm implementing negative shift or
       # reverse shift or left shift
       for i in encoded_message:
            lowerCAmelCase		:					Dict  	=     self.__key_list.index(lowerCamelCase__				)
            decoded_message += self.__key_list[
                (position - self.__shift_key) % -len(self.__key_list				)
            ]

       return decoded_message





  def       _A							(							self    :	str						,  lowerCamelCase__    :	str				):
       lowerCAmelCase		:					List[Any]  	=     ''''''

       # encoding shift like Caesar cipher algorithm implementing positive shift or
       # forward shift or right shift
       for i in plaintext:
            lowerCAmelCase		:					Any  	=     self.__key_list.index(lowerCamelCase__				)
            encoded_message += self.__key_list[
                (position + self.__shift_key) % len(self.__key_list				)
            ]

       return encoded_message



def     UpperCAmelCase__							(       __magic_name__						:     str = "Hello, this is a modified Caesar cipher"  ):


     '''simple docstring'''

     lowerCAmelCase		:					Optional[int]  	=     ShuffledShiftCipher()
     return cipa.decrypt(cipa.encrypt(__magic_name__  )  )


if __name__ == "__main__":
  import doctest

  doctest.testmod()


from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
		from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore


class 		__magic_name__   (						snake_case    ):
		_lowerCAmelCase		=	c_float





		@property
		def       _A							(							self    :	int				):
							return sizeof(self.value				)



def     UpperCAmelCase__							(       __magic_name__						:     int							,  __magic_name__						:     int							,  __magic_name__						:     int = 0  ):


					'''simple docstring'''

					if dimension <= 0:
										lowerCAmelCase		:					Tuple  	=     fixed_dimension

					dimension -= num_token_to_add
					return dimension
def     UpperCAmelCase__							(       __magic_name__						:     int							,  __magic_name__						:     ParameterFormat  ):


					'''simple docstring'''

					return num_parameters * dtype.size
def     UpperCAmelCase__							(       __magic_name__						:     str  ):


					'''simple docstring'''

					from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

					try:
										return AutoProcessor.from_pretrained(__magic_name__  )
					except (ValueError, OSError, KeyError):
										lowerCAmelCase	,							lowerCAmelCase		:					Any  	=     None, None
										try:
															lowerCAmelCase		:					Union[str, Any]  	=     AutoTokenizer.from_pretrained(__magic_name__  )
										except (OSError, KeyError):
															pass
										try:
															lowerCAmelCase		:					List[Any]  	=     AutoFeatureExtractor.from_pretrained(__magic_name__  )
										except (OSError, KeyError):
															pass

										if tokenizer is not None and feature_extractor is not None:
															raise ValueError(
															    f'''Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor.'''  )
										elif tokenizer is None and feature_extractor is None:
															return None
										elif tokenizer is not None:
															return tokenizer
										else:
															return feature_extractor
