


'''simple docstring'''

from __future__ import annotations

from string import ascii_letters



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					str     ,		_UpperCamelCase   :					int     ,		_UpperCamelCase   :					str | None = None )		->       str:





   '''simple docstring'''







   UpperCamelCase__			    =    alphabet or ascii_letters

   # The final result string
   UpperCamelCase__			    =    ""

   for character in input_string:
      if character not in alpha:
         # Append without encryption if character is not in the alphabet
         result += character
      else:
         # Get the index of the new key and make sure it isn't too large
         UpperCamelCase__			    =    (alpha.index(_UpperCamelCase ) + key) % len(_UpperCamelCase )

         # Append the encoded character to the alphabet
         result += alpha[new_key]

   return result



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					str     ,		_UpperCamelCase   :					int     ,		_UpperCamelCase   :					str | None = None )		->       str:





   '''simple docstring'''







   key *= -1

   return encrypt(_UpperCamelCase     ,		_UpperCamelCase     ,		_UpperCamelCase )



def 							SCREAMING_SNAKE_CASE__(		_UpperCamelCase   :					str     ,		_UpperCamelCase   :					str | None = None )		->       dict[int, str]:





   '''simple docstring'''







   UpperCamelCase__			    =    alphabet or ascii_letters

   # To store data on all the combinations
   UpperCamelCase__			    =    {}

   # Cycle through each combination
   for key in range(1     ,		len(_UpperCamelCase ) + 1 ):
      # Decrypt the message and store the result in the data
      UpperCamelCase__			    =    decrypt(_UpperCamelCase     ,		_UpperCamelCase     ,		_UpperCamelCase )

   return brute_force_data


if __name__ == "__main__":
       while True:
              print(F"""\n{'-' * 10}\n Menu\n{'-' * 10}""")
              print(*["1.Encrypt", "2.Decrypt", "3.BruteForce", "4.Quit"], sep="\n")

              # get user input
              __lowercase:		List[str]    						=  input("\nWhat would you like to do?: ").strip() or "4"

              # run functions based on what the user chose
              if choice not in ("1", "2", "3", "4"):
                     print("Invalid choice, please enter a valid choice")
              elif choice == "1":
                     __lowercase:		Optional[Any]    						=  input("Please enter the string to be encrypted: ")
                     __lowercase:		Tuple    						=  int(input("Please enter off-set: ").strip())

                     print(encrypt(input_string, key))
              elif choice == "2":
                     __lowercase:		Any    						=  input("Please enter the string to be decrypted: ")
                     __lowercase:		Union[str, Any]    						=  int(input("Please enter off-set: ").strip())

                     print(decrypt(input_string, key))
              elif choice == "3":
                     __lowercase:		List[Any]    						=  input("Please enter the string to be decrypted: ")
                     __lowercase:		Optional[Any]    						=  brute_force(input_string)

                     for key, value in brute_force_data.items():
                            print(F"""Key: {key} | Message: {value}""")

              elif choice == "4":
                     print("Goodbye.")
                     break





"""simple docstring"""

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

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


if is_sentencepiece_available():
		from .tokenization_xglm import XGLMTokenizer
else:
		_lowerCamelCase	:      Union[str, Any]   =							None


_lowerCamelCase	:      Optional[Any]   =							logging.get_logger(__name__)

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

_lowerCamelCase	:      Union[str, Any]   =							{
    'vocab_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json',
    },
}

_lowerCamelCase	:      Dict   =							{
    'facebook/xglm-564M': 2048,
}

class 							lowercase   (     __UpperCAmelCase):
				__lowerCAmelCase     :     Optional[int]								= VOCAB_FILES_NAMES
				__lowerCAmelCase     :     Tuple								= PRETRAINED_VOCAB_FILES_MAP
				__lowerCAmelCase     :     List[Any]								= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__lowerCAmelCase     :     Union[str, Any]								= ["""input_ids""", """attention_mask"""]
				__lowerCAmelCase     :     List[str]								= XGLMTokenizer







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



					"""simple docstring"""

					A_	:					Tuple						 =		7
					A_	:					Dict						 =		[F"""<madeupword{i}>""" for i in range(self.num_madeup_words							)]

					A_	:					str						 =		kwargs.get('''additional_special_tokens'''   ,  []							)
					kwargs["additional_special_tokens"] += [
					    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
					]

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

					A_	:					Tuple						 =		vocab_file
					A_	:					str						 =		False if not self.vocab_file else True







				def        a_	(				self :       List[Any]   ,  _lowerCamelCase :       List[int]   ,  _lowerCamelCase :       Optional[List[int]] = None							):



					"""simple docstring"""

					if token_ids_a is None:
						return [self.sep_token_id] + token_ids_a
					A_	:					List[Any]						 =		[self.sep_token_id]
					return sep + token_ids_a + sep + sep + token_ids_a







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



					"""simple docstring"""

					A_	:					Dict						 =		[self.sep_token_id]

					if token_ids_a is None:
						return len(sep + token_ids_a							) * [0]
					return len(sep + token_ids_a + sep + sep + token_ids_a							) * [0]







				def        a_	(				self :       List[str]   ,  _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_	:					Tuple						 =		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,)





