





import os
import re
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowercase     :			Any     						=	logging.get_logger(__name__)
lowercase     :			int     						=	{"""vocab_file""": """spiece.model"""}

lowercase     :			Tuple     						=	{
    """vocab_file""": {
        """google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/spiece.model""",
        """google/fnet-large""": """https://huggingface.co/google/fnet-large/resolve/main/spiece.model""",
    },
}

lowercase     :			Union[str, Any]     						=	{
    """google/fnet-base""": 512,
    """google/fnet-large""": 512,
}

lowercase     :			Optional[int]     						=	"""▁"""

class 			__A(    __UpperCAmelCase			):
     __A							=							VOCAB_FILES_NAMES
     __A							=							PRETRAINED_VOCAB_FILES_MAP
     __A							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __A							=							["""input_ids""", """token_type_ids"""]

     def __init__(   self,							A,							A=False,							A=True,							A=True,							A="<unk>",							A="[SEP]",							A="<pad>",							A="[CLS]",							A="[MASK]",							A = None,							**A,							):





            """simple docstring"""

            _UpperCamelCase														=    (
                AddedToken(A,							lstrip=A,							rstrip=A,							normalized=A   )
                if isinstance(A,							A   )
                else mask_token
            )

            _UpperCamelCase														=    {} if sp_model_kwargs is None else sp_model_kwargs

            super().__init__(
                do_lower_case=A,							remove_space=A,							keep_accents=A,							unk_token=A,							sep_token=A,							pad_token=A,							cls_token=A,							mask_token=A,							sp_model_kwargs=self.sp_model_kwargs,							**A,							)

            _UpperCamelCase														=    do_lower_case
            _UpperCamelCase														=    remove_space
            _UpperCamelCase														=    keep_accents
            _UpperCamelCase														=    vocab_file

            _UpperCamelCase														=    spm.SentencePieceProcessor(**self.sp_model_kwargs   )
            self.sp_model.Load(A   )

     @property
     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            return len(self.sp_model   )

     def 						_UpperCamelCase  (   self   ):





            """simple docstring"""

            _UpperCamelCase														=    {self.convert_ids_to_tokens(A   ): i for i in range(self.vocab_size   )}
            vocab.update(self.added_tokens_encoder   )
            return vocab

     def __getstate__(   self   ):





            """simple docstring"""

            _UpperCamelCase														=    self.__dict__.copy()
            _UpperCamelCase														=    None
            return state

     def __setstate__(   self,							A   ):





            """simple docstring"""

            _UpperCamelCase														=    d

            # for backward compatibility
            if not hasattr(self,							'''sp_model_kwargs'''   ):
                   _UpperCamelCase														=    {}

            _UpperCamelCase														=    spm.SentencePieceProcessor(**self.sp_model_kwargs   )
            self.sp_model.Load(self.vocab_file   )

     def 						_UpperCamelCase  (   self,							A   ):





            """simple docstring"""

            if self.remove_space:
                   _UpperCamelCase														=    ''' '''.join(inputs.strip().split()   )
            else:
                   _UpperCamelCase														=    inputs
            _UpperCamelCase														=    outputs.replace('''``''',							'''\"'''   ).replace('''\'\'''',							'''\"'''   )

            if not self.keep_accents:
                   _UpperCamelCase														=    unicodedata.normalize('''NFKD''',							A   )
                   _UpperCamelCase														=    ''''''.join([c for c in outputs if not unicodedata.combining(A   )]   )
            if self.do_lower_case:
                   _UpperCamelCase														=    outputs.lower()

            return outputs

     def 						_UpperCamelCase  (   self,							A   ):





            """simple docstring"""

            _UpperCamelCase														=    self.preprocess_text(A   )
            _UpperCamelCase														=    self.sp_model.encode(A,							out_type=A   )
            _UpperCamelCase														=    []
            for piece in pieces:
                   if len(A   ) > 1 and piece[-1] == str(''','''   ) and piece[-2].isdigit():
                          _UpperCamelCase														=    self.sp_model.EncodeAsPieces(piece[:-1].replace(A,							''''''   )   )
                          if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                                 if len(cur_pieces[0]   ) == 1:
                                        _UpperCamelCase														=    cur_pieces[1:]
                                 else:
                                        _UpperCamelCase														=    cur_pieces[0][1:]
                          cur_pieces.append(piece[-1]   )
                          new_pieces.extend(A   )
                   else:
                          new_pieces.append(A   )

            return new_pieces

     def 						_UpperCamelCase  (   self,							A   ):





            """simple docstring"""

            return self.sp_model.PieceToId(A   )

     def 						_UpperCamelCase  (   self,							A   ):





            """simple docstring"""

            return self.sp_model.IdToPiece(A   )

     def 						_UpperCamelCase  (   self,							A   ):





            """simple docstring"""

            _UpperCamelCase														=    []
            _UpperCamelCase														=    ''''''
            _UpperCamelCase														=    False
            for token in tokens:
                   # make sure that special tokens are not decoded using sentencepiece model
                   if token in self.all_special_tokens:
                          if not prev_is_special:
                                 out_string += " "
                          out_string += self.sp_model.decode(A   ) + token
                          _UpperCamelCase														=    True
                          _UpperCamelCase														=    []
                   else:
                          current_sub_tokens.append(A   )
                          _UpperCamelCase														=    False
            out_string += self.sp_model.decode(A   )
            return out_string.strip()

     def 						_UpperCamelCase  (   self,							A,							A = False,							A = None,							A = True,							**A,							):





            """simple docstring"""

            _UpperCamelCase														=    kwargs.pop('''use_source_tokenizer''',							A   )

            _UpperCamelCase														=    self.convert_ids_to_tokens(A,							skip_special_tokens=A   )

            # To avoid mixing byte-level and unicode for byte-level BPT
            # we need to build string separately for added tokens and byte-level tokens
            # cf. https://github.com/huggingface/transformers/issues/1133
            _UpperCamelCase														=    []
            _UpperCamelCase														=    []
            for token in filtered_tokens:
                   if skip_special_tokens and token in self.all_special_ids:
                          continue
                   if token in self.added_tokens_encoder:
                          if current_sub_text:
                                 sub_texts.append(self.convert_tokens_to_string(A   )   )
                                 _UpperCamelCase														=    []
                          sub_texts.append(A   )
                   else:
                          current_sub_text.append(A   )
            if current_sub_text:
                   sub_texts.append(self.convert_tokens_to_string(A   )   )

            # Mimic the behavior of the Rust tokenizer:
            # No space after <unk>
            if spaces_between_special_tokens:
                   _UpperCamelCase														=    re.sub(R'''(<unk>) ''',							R'''\1''',							''' '''.join(A   )   )
            else:
                   _UpperCamelCase														=    ''''''.join(A   )

            _UpperCamelCase														=    (
                clean_up_tokenization_spaces
                if clean_up_tokenization_spaces is not None
                else self.clean_up_tokenization_spaces
            )
            if clean_up_tokenization_spaces:
                   _UpperCamelCase														=    self.clean_up_tokenization(A   )
                   return clean_text
            else:
                   return text

     def 						_UpperCamelCase  (   self,							A,							A = None   ):





            """simple docstring"""

            _UpperCamelCase														=    [self.sep_token_id]
            _UpperCamelCase														=    [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 						_UpperCamelCase  (   self,							A,							A = None,							A = False   ):





            """simple docstring"""

            if already_has_special_tokens:
                   return super().get_special_tokens_mask(
                       token_ids_a=A,							token_ids_a=A,							already_has_special_tokens=A   )

            if token_ids_a is not None:
                   return [1] + ([0] * len(A   )) + [1] + ([0] * len(A   )) + [1]
            return [1] + ([0] * len(A   )) + [1]

     def 						_UpperCamelCase  (   self,							A,							A = None   ):





            """simple docstring"""

            _UpperCamelCase														=    [self.sep_token_id]
            _UpperCamelCase														=    [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 						_UpperCamelCase  (   self,							A,							A = None   ):





            """simple docstring"""

            if not os.path.isdir(A   ):
                   logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
                   return
            _UpperCamelCase														=    os.path.join(
                A,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )

            if os.path.abspath(self.vocab_file   ) != os.path.abspath(A   ) and os.path.isfile(self.vocab_file   ):
                   copyfile(self.vocab_file,							A   )
            elif not os.path.isfile(self.vocab_file   ):
                   with open(A,							'''wb'''   ) as fi:
                          _UpperCamelCase														=    self.sp_model.serialized_model_proto()
                          fi.write(A   )

            return (out_vocab_file,)








'''simple docstring'''







from __future__ import annotations

import random
import string


class       lowerCAmelCase			:




		def __init__(					self       ,    UpperCamelCase = None   ):
								_SCREAMING_SNAKE_CASE					=			passcode or self.__passcode_creator()
								_SCREAMING_SNAKE_CASE					=			self.__make_key_list()
								_SCREAMING_SNAKE_CASE					=			self.__make_shift_key()




		def __str__(					self   ):
								return "".join(self.__passcode   )




		def      lowercase							(					self       ,    UpperCamelCase   ):
								for i in range(1       ,    len(UpperCamelCase   )       ,    2   ):
														iterlist[i] *= -1
								return iterlist




		def      lowercase							(					self   ):
								_SCREAMING_SNAKE_CASE					=			string.ascii_letters + string.digits
								_SCREAMING_SNAKE_CASE					=			[random.choice(UpperCamelCase   ) for _ in range(random.randint(10       ,    20   )   )]
								return password




		def      lowercase							(					self   ):
								_SCREAMING_SNAKE_CASE					=			(
								    string.ascii_letters + string.digits + string.punctuation + " \t\n"
								)

								_SCREAMING_SNAKE_CASE					=			[]

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

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

														# 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      lowercase							(					self   ):
								_SCREAMING_SNAKE_CASE					=			sum(self.__neg_pos([ord(UpperCamelCase   ) for x in self.__passcode]   )   )
								return num if num > 0 else len(self.__passcode   )




		def      lowercase							(					self       ,    UpperCamelCase   ):
								_SCREAMING_SNAKE_CASE					=			""

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

								return decoded_message




		def      lowercase							(					self       ,    UpperCamelCase   ):
								_SCREAMING_SNAKE_CASE					=			""

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

								return encoded_message



def       _a		(						_SCREAMING_SNAKE_CASE		: str = "Hello, this is a modified Caesar cipher"	):
						_SCREAMING_SNAKE_CASE					=			ShuffledShiftCipher()
						return cipa.decrypt(cipa.encrypt(_SCREAMING_SNAKE_CASE	)	)


if __name__ == "__main__":
						import doctest

						doctest.testmod()