






import os
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


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

SCREAMING_SNAKE_CASE__   :      str				=		{
    """vocab_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/spiece.model""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/spiece.model""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/spiece.model""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/spiece.model""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model""",
    }
}

SCREAMING_SNAKE_CASE__   :      Union[str, Any]				=		{
    """albert-base-v1""": 5_12,
    """albert-large-v1""": 5_12,
    """albert-xlarge-v1""": 5_12,
    """albert-xxlarge-v1""": 5_12,
    """albert-base-v2""": 5_12,
    """albert-large-v2""": 5_12,
    """albert-xlarge-v2""": 5_12,
    """albert-xxlarge-v2""": 5_12,
}

SCREAMING_SNAKE_CASE__   :      List[str]				=		"""▁"""
class     lowerCamelCase_					(   lowerCamelCase			):
				a__       							=	VOCAB_FILES_NAMES
				a__       							=	PRETRAINED_VOCAB_FILES_MAP
				a__       							=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES







				def __init__(    self							,       __lowerCAmelCase							,       __lowerCAmelCase=True							,       __lowerCAmelCase=True							,       __lowerCAmelCase=False							,       __lowerCAmelCase="[CLS]"							,       __lowerCAmelCase="[SEP]"							,       __lowerCAmelCase="<unk>"							,       __lowerCAmelCase="[SEP]"							,       __lowerCAmelCase="<pad>"							,       __lowerCAmelCase="[CLS]"							,       __lowerCAmelCase="[MASK]"							,       __lowerCAmelCase = None							,       **__lowerCAmelCase							,       ):
								"""simple docstring"""
								# Mask token behave like a normal word, i.e. include the space before it and
								# is included in the raw text, there should be a match in a non-normalized sentence.
								__magic_name__		:Any   =   (
								    AddedToken(__lowerCAmelCase							,       lstrip=__lowerCAmelCase							,       rstrip=__lowerCAmelCase							,       normalized=__lowerCAmelCase  )
								    if isinstance(__lowerCAmelCase							,       __lowerCAmelCase  )
								    else mask_token
								)

								__magic_name__		:int   =   {} if sp_model_kwargs is None else sp_model_kwargs

								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							,       sp_model_kwargs=self.sp_model_kwargs							,       **__lowerCAmelCase							,       )

								__magic_name__		:Optional[Any]   =   do_lower_case
								__magic_name__		:Any   =   remove_space
								__magic_name__		:List[str]   =   keep_accents
								__magic_name__		:int   =   vocab_file

								__magic_name__		:Optional[int]   =   spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(__lowerCAmelCase  )







				@property
				def       A						(    self  ):
								"""simple docstring"""
								return len(self.sp_model  )







				def       A						(    self  ):
								"""simple docstring"""
								__magic_name__		:Tuple   =   {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  ):
								"""simple docstring"""
								__magic_name__		:Tuple   =   self.__dict__.copy()
								__magic_name__		:Union[str, Any]   =   None
								return state







				def __setstate__(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								__magic_name__		:List[Any]   =   d

								# for backward compatibility
								if not hasattr(self							,       '''sp_model_kwargs'''  ):
												__magic_name__		:Optional[Any]   =   {}

								__magic_name__		:int   =   spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(self.vocab_file  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								if self.remove_space:
												__magic_name__		:List[str]   =   ''' '''.join(inputs.strip().split()  )
								else:
												__magic_name__		:Optional[int]   =   inputs
								__magic_name__		:Dict   =   outputs.replace('''``'''							,       '''"'''  ).replace('''\'\''''							,       '''"'''  )

								if not self.keep_accents:
												__magic_name__		:str   =   unicodedata.normalize('''NFKD'''							,       __lowerCAmelCase  )
												__magic_name__		:Any   =   ''''''.join([c for c in outputs if not unicodedata.combining(__lowerCAmelCase  )]  )
								if self.do_lower_case:
												__magic_name__		:Optional[Any]   =   outputs.lower()

								return outputs







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								__magic_name__		:Optional[int]   =   self.preprocess_text(__lowerCAmelCase  )
								__magic_name__		:Dict   =   self.sp_model.encode(__lowerCAmelCase							,       out_type=__lowerCAmelCase  )
								__magic_name__		:Any   =   []
								for piece in pieces:
												if len(__lowerCAmelCase  ) > 1 and piece[-1] == str(''','''  ) and piece[-2].isdigit():
																__magic_name__		:List[str]   =   self.sp_model.EncodeAsPieces(piece[:-1].replace(__lowerCAmelCase							,       ''''''  )  )
																if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																				if len(cur_pieces[0]  ) == 1:
																								__magic_name__		:str   =   cur_pieces[1:]
																				else:
																								__magic_name__		:List[Any]   =   cur_pieces[0][1:]
																cur_pieces.append(piece[-1]  )
																new_pieces.extend(__lowerCAmelCase  )
												else:
																new_pieces.append(__lowerCAmelCase  )

								return new_pieces







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								return self.sp_model.PieceToId(__lowerCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								return self.sp_model.IdToPiece(__lowerCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								__magic_name__		:Dict   =   []
								__magic_name__		:List[str]   =   ''''''
								__magic_name__		:List[Any]   =   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(__lowerCAmelCase  ) + token
																__magic_name__		:Union[str, Any]   =   True
																__magic_name__		:Tuple   =   []
												else:
																current_sub_tokens.append(__lowerCAmelCase  )
																__magic_name__		:Optional[int]   =   False
								out_string += self.sp_model.decode(__lowerCAmelCase  )
								return out_string.strip()







				def       A						(    self							,       __lowerCAmelCase							,       __lowerCAmelCase = None  ):
								"""simple docstring"""
								__magic_name__		:Any   =   [self.sep_token_id]
								__magic_name__		:List[Any]   =   [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							,       __lowerCAmelCase							,       __lowerCAmelCase = None							,       __lowerCAmelCase = False  ):
								"""simple docstring"""

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

								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							,       __lowerCAmelCase							,       __lowerCAmelCase = None  ):
								"""simple docstring"""
								__magic_name__		:Union[str, Any]   =   [self.sep_token_id]
								__magic_name__		:str   =   [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							,       __lowerCAmelCase							,       __lowerCAmelCase = None  ):
								"""simple docstring"""
								if not os.path.isdir(__lowerCAmelCase  ):
												logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
												return
								__magic_name__		:int   =   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  ) and os.path.isfile(self.vocab_file  ):
												copyfile(self.vocab_file							,       __lowerCAmelCase  )
								elif not os.path.isfile(self.vocab_file  ):
												with open(__lowerCAmelCase							,       '''wb'''  ) as fi:
																__magic_name__		:int   =   self.sp_model.serialized_model_proto()
																fi.write(__lowerCAmelCase  )

								return (out_vocab_file,)













def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> bool:




    """simple docstring"""




    if not isinstance(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
        raise ValueError('check_bouncy() accepts only integer arguments'				)
    _A     =							str(_SCREAMING_SNAKE_CASE				)
    _A     =							''.join(sorted(_SCREAMING_SNAKE_CASE				)				)
    return sorted_str_n != str_n and sorted_str_n[::-1] != str_n





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE = 99				)							-> int:




    """simple docstring"""




    if not 0 < percent < 100:
        raise ValueError('solution() only accepts values from 0 to 100'				)
    _A     =							0
    _A     =							1

    while True:
        if check_bouncy(_SCREAMING_SNAKE_CASE				):
            bouncy_num += 1
        if (bouncy_num / num) * 100 >= percent:
            return num
        num += 1


if __name__ == "__main__":
 from doctest import testmod

 testmod()
 print(f"{solution(99)}")





