code: import random
  import sys
  
  from . import cryptomath_module as cryptomath
  
  A_:      Optional[int]        =			(
      R' !"#$%&\'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`'
      R'abcdefghijklmnopqrstuvwxyz{|}~'
  )
  
  
  def 					__lowerCAmelCase			(  _A ,_A ,_A					)     ->   None:
  
  
  
  							"""simple docstring"""
  
  
  							if mode == "encrypt":
  														if key_a == 1:
  																					sys.exit(
  																					    """The affine cipher becomes weak when key """
  																					    """A is set to 1. Choose different key"""					)
  														if key_b == 0:
  																					sys.exit(
  																					    """The affine cipher becomes weak when key """
  																					    """B is set to 0. Choose different key"""					)
  							if key_a < 0 or key_b < 0 or key_b > len(snake_case__					) - 1:
  														sys.exit(
  														    """Key A must be greater than 0 and key B must """
  														    f'''be between 0 and {len(snake_case__					) - 1}.'''					)
  							if cryptomath.gcd(snake_case__ ,len(snake_case__					)					) != 1:
  														sys.exit(
  														    f'''Key A {key_a} and the symbol set size {len(snake_case__					)} '''
  														    """are not relatively prime. Choose a different key."""					)
  
  
  def 					__lowerCAmelCase			(  _A ,_A					)     ->   str:
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	divmod(snake_case__ ,len(snake_case__					)					)
  							check_keys(snake_case__ ,snake_case__ ,"""encrypt"""					)
  							_lowercase				=	''
  							for symbol in message:
  														if symbol in SYMBOLS:
  																					_lowercase				=	SYMBOLS.find(snake_case__					)
  																					cipher_text += SYMBOLS[(sym_index * key_a + key_b) % len(snake_case__					)]
  														else:
  																					cipher_text += symbol
  							return cipher_text
  
  
  def 					__lowerCAmelCase			(  _A ,_A					)     ->   str:
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	divmod(snake_case__ ,len(snake_case__					)					)
  							check_keys(snake_case__ ,snake_case__ ,"""decrypt"""					)
  							_lowercase				=	''
  							_lowercase				=	cryptomath.find_mod_inverse(snake_case__ ,len(snake_case__					)					)
  							for symbol in message:
  														if symbol in SYMBOLS:
  																					_lowercase				=	SYMBOLS.find(snake_case__					)
  																					plain_text += SYMBOLS[
  																					    (sym_index - key_b) * mod_inverse_of_key_a % len(snake_case__					)
  																					]
  														else:
  																					plain_text += symbol
  							return plain_text
  
  
  def 					__lowerCAmelCase			(  )     ->   int:
  
  
  
  							"""simple docstring"""
  
  
  							while True:
  														_lowercase				=	random.randint(2 ,len(snake_case__					)					)
  														_lowercase				=	random.randint(2 ,len(snake_case__					)					)
  														if cryptomath.gcd(snake_case__ ,len(snake_case__					)					) == 1 and key_b % len(snake_case__					) != 0:
  																					return key_b * len(snake_case__					) + key_b
  
  
  def 					__lowerCAmelCase			(  )     ->   None:
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	input("""Enter message: """					).strip()
  							_lowercase				=	int(input("""Enter key [2000 - 9000]: """					).strip()					)
  							_lowercase				=	input("""Encrypt/Decrypt [E/D]: """					).strip().lower()
  
  							if mode.startswith("""e"""					):
  														_lowercase				=	'encrypt'
  														_lowercase				=	encrypt_message(snake_case__ ,snake_case__					)
  							elif mode.startswith("""d"""					):
  														_lowercase				=	'decrypt'
  														_lowercase				=	decrypt_message(snake_case__ ,snake_case__					)
  							print(f'''\n{mode.title()}ed text: \n{translated}'''					)
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  				# main()
  
  
  
style_context: 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 _lowercase					(       _UpperCAmelCase						):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  							lowerCAmelCase__       =					c_float
  
  
  
  							@property
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														return sizeof(self.value  )
  
  
  
  
  
  
  def 					__lowerCAmelCase			(  _A ,_A ,_A = 0					):
  
  
  
  							"""simple docstring"""
  
  
  							if dimension <= 0:
  														_lowercase				=	fixed_dimension
  
  							dimension -= num_token_to_add
  							return dimension
  
  
  def 					__lowerCAmelCase			(  _A ,_A					):
  
  
  
  							"""simple docstring"""
  
  
  							return num_parameters * dtype.size
  
  
  
  
  
  
  
  def 					__lowerCAmelCase			(  _A					):
  
  
  
  							"""simple docstring"""
  
  
  							from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore
  
  							try:
  														return AutoProcessor.from_pretrained(_A					)
  							except (ValueError, OSError, KeyError):
  														_lowercase				,       _lowercase				=	None, None
  														try:
  																					_lowercase				=	AutoTokenizer.from_pretrained(_A					)
  														except (OSError, KeyError):
  																					pass
  														try:
  																					_lowercase				=	AutoFeatureExtractor.from_pretrained(_A					)
  														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
  
  
  