'''simple docstring'''

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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_A			:      int					      =				logging.get_logger(__name__)

_A			:      Any					      =				{'vocab_file': 'sentencepiece.model'}

_A			:      Any					      =				{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
}

_A			:      str					      =				{
    'google/rembert': 256,
}







class 				_lowercase     (				_UpperCamelCase			):


 '''simple docstring'''






 _SCREAMING_SNAKE_CASE     :       int      	=					VOCAB_FILES_NAMES
 _SCREAMING_SNAKE_CASE     :       List[str]      	=					PRETRAINED_VOCAB_FILES_MAP
 _SCREAMING_SNAKE_CASE     :       Any      	=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 def __init__(      self   :	Optional[int]      ,       SCREAMING_SNAKE_CASE__   :	List[Any]      ,       SCREAMING_SNAKE_CASE__   :	str=False      ,       SCREAMING_SNAKE_CASE__   :	int=True      ,       SCREAMING_SNAKE_CASE__   :	List[Any]=True      ,       SCREAMING_SNAKE_CASE__   :	Optional[int]="[CLS]"      ,       SCREAMING_SNAKE_CASE__   :	Dict="[SEP]"      ,       SCREAMING_SNAKE_CASE__   :	Optional[Any]="[UNK]"      ,       SCREAMING_SNAKE_CASE__   :	List[str]="[SEP]"      ,       SCREAMING_SNAKE_CASE__   :	Union[str, Any]="[PAD]"      ,       SCREAMING_SNAKE_CASE__   :	Tuple="[CLS]"      ,       SCREAMING_SNAKE_CASE__   :	Union[str, Any]="[MASK]"      ,       **SCREAMING_SNAKE_CASE__   :	int      ,       )  ->    Tuple:
  super().__init__(
      do_lower_case=__lowerCamelCase      ,       remove_space=__lowerCamelCase      ,       keep_accents=__lowerCamelCase      ,       bos_token=__lowerCamelCase      ,       eos_token=__lowerCamelCase      ,       unk_token=__lowerCamelCase      ,       sep_token=__lowerCamelCase      ,       pad_token=__lowerCamelCase      ,       cls_token=__lowerCamelCase      ,       mask_token=__lowerCamelCase      ,       **__lowerCamelCase      ,       )

  __lowerCAmelCase											=						do_lower_case
  __lowerCAmelCase											=						remove_space
  __lowerCAmelCase											=						keep_accents
  __lowerCAmelCase											=						vocab_file

  __lowerCAmelCase											=						spm.SentencePieceProcessor()
  self.sp_model.Load(__lowerCamelCase							)
 @property
 def a					(      self   :	Union[str, Any]							)  ->    str:
  return len(self.sp_model							)
 def a					(      self   :	List[str]							)  ->    List[Any]:
  __lowerCAmelCase											=						{self.convert_ids_to_tokens(__lowerCamelCase							): i for i in range(self.vocab_size							)}
  vocab.update(self.added_tokens_encoder							)
  return vocab
 def __getstate__(      self   :	List[Any]							)  ->    Dict:
  __lowerCAmelCase											=						self.__dict__.copy()
  __lowerCAmelCase											=						None
  return state
 def __setstate__(      self   :	List[str]      ,       SCREAMING_SNAKE_CASE__   :	Dict							)  ->    Any:
  __lowerCAmelCase											=						d
  __lowerCAmelCase											=						spm.SentencePieceProcessor()
  self.sp_model.Load(self.vocab_file							)
 def a					(      self   :	int      ,       SCREAMING_SNAKE_CASE__   :	List[Any]      ,       SCREAMING_SNAKE_CASE__   :	Optional[int]=False							)  ->    str:
  __lowerCAmelCase											=						self.sp_model.EncodeAsPieces(__lowerCamelCase							)
  return pieces
 def a					(      self   :	str      ,       SCREAMING_SNAKE_CASE__   :	Dict							)  ->    Optional[int]:
  return self.sp_model.PieceToId(__lowerCamelCase							)
 def a					(      self   :	Optional[Any]      ,       SCREAMING_SNAKE_CASE__   :	Tuple							)  ->    Optional[Any]:
  return self.sp_model.IdToPiece(__lowerCamelCase							)
 def a					(      self   :	Optional[int]      ,       SCREAMING_SNAKE_CASE__   :	List[Any]							)  ->    List[str]:
  __lowerCAmelCase											=						self.sp_model.decode_pieces(__lowerCamelCase							)
  return out_string
 def a					(      self   :	Dict      ,       SCREAMING_SNAKE_CASE__   :	List[int]      ,       SCREAMING_SNAKE_CASE__   :	Optional[List[int]] = None							)  ->    List[int]:
  __lowerCAmelCase											=						[self.sep_token_id]
  __lowerCAmelCase											=						[self.cls_token_id]
  if token_ids_a is None:
   return cls + token_ids_a + sep
  return cls + token_ids_a + sep + token_ids_a + sep
 def a					(      self   :	Dict      ,       SCREAMING_SNAKE_CASE__   :	List[int]      ,       SCREAMING_SNAKE_CASE__   :	Optional[List[int]] = None      ,       SCREAMING_SNAKE_CASE__   :	bool = False							)  ->    List[int]:

  if already_has_special_tokens:
   if token_ids_a is not None:
    raise ValueError(
        """You should not supply a second sequence if the provided sequence of """
        """ids is already formatted with special tokens for the model."""							)
   return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

  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   :	Union[str, Any]      ,       SCREAMING_SNAKE_CASE__   :	List[int]      ,       SCREAMING_SNAKE_CASE__   :	Optional[List[int]] = None							)  ->    List[int]:
  __lowerCAmelCase											=						[self.sep_token_id]
  __lowerCAmelCase											=						[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   :	str      ,       SCREAMING_SNAKE_CASE__   :	str      ,       SCREAMING_SNAKE_CASE__   :	Optional[str] = None							)  ->    Tuple[str]:
  if not os.path.isdir(__lowerCamelCase							):
   logger.error("""Vocabulary path ({}) should be a directory""".format(__lowerCamelCase							)							)
   return
  __lowerCAmelCase											=						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,)












def 			__magic_name__				( A		:					str   ):






			'''simple docstring'''







			a    =			""
			for ch in key:
						if ch == " " or ch not in key_no_dups and ch.isalpha():
									key_no_dups += ch
			return key_no_dups




def 			__magic_name__				( A		:					str   ):






			'''simple docstring'''







			a    =			[chr(i + 65   ) for i in range(26   )]
			# Remove duplicate characters from key
			a    =			remove_duplicates(key.upper()   )
			a    =			len(A   )
			# First fill cipher with key characters
			a    =			{alphabet[i]: char for i, char in enumerate(A   )}
			# Then map remaining characters in alphabet to
			# the alphabet from the beginning
			for i in range(len(A   ),  26   ):
						a    =			alphabet[i - offset]
						# Ensure we are not mapping letters to letters previously mapped
						while char in key:
									offset -= 1
									a    =			alphabet[i - offset]
						a    =			char
			return cipher_alphabet




def 			__magic_name__				( A		:					str,  A		:					dict[str, str]   ):






			'''simple docstring'''







			return "".join(cipher_map.get(A,  A   ) for ch in message.upper()   )




def 			__magic_name__				( A		:					str,  A		:					dict[str, str]   ):






			'''simple docstring'''







			a    =			{v: k for k, v in cipher_map.items()}
			return "".join(rev_cipher_map.get(A,  A   ) for ch in message.upper()   )




def 			__magic_name__				( ):






			'''simple docstring'''







			a    =			input("Enter message to encode or decode: "   ).strip()
			a    =			input("Enter keyword: "   ).strip()
			a    =			input("Encipher or decipher? E/D:"   ).strip()[0].lower()
			try:
						a    =			{"e": encipher, "d": decipher}[option]
			except KeyError:
						raise KeyError("invalid input option"   )
			a    =			create_cipher_map(A   )
			print(func(A,  A   )   )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()






