

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 SPIECE_UNDERLINE, logging


UpperCamelCase__		 =     logging.get_logger(__name__)

UpperCamelCase__		 =     {'''vocab_file''': '''spiece.model'''}

UpperCamelCase__		 =     {
    '''vocab_file''': {
        '''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model''',
        '''xlnet-large-cased''': '''https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model''',
    }
}

UpperCamelCase__		 =     {
    '''xlnet-base-cased''': None,
    '''xlnet-large-cased''': None,
}

# Segments (not really needed)
UpperCamelCase__		 =     0
UpperCamelCase__		 =     1
UpperCamelCase__		 =     2
UpperCamelCase__		 =     3
UpperCamelCase__		 =     4

class     __snake_case    (				snake_case__  ):
       """simple docstring"""







       __SCREAMING_SNAKE_CASE				    =							VOCAB_FILES_NAMES
       __SCREAMING_SNAKE_CASE				    =							PRETRAINED_VOCAB_FILES_MAP
       __SCREAMING_SNAKE_CASE				    =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __SCREAMING_SNAKE_CASE				    =							"left"


       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase=False      , _UpperCamelCase=True      , _UpperCamelCase=False      , _UpperCamelCase="<s>"      , _UpperCamelCase="</s>"      , _UpperCamelCase="<unk>"      , _UpperCamelCase="<sep>"      , _UpperCamelCase="<pad>"      , _UpperCamelCase="<cls>"      , _UpperCamelCase="<mask>"      , _UpperCamelCase=["<eop>", "<eod>"]      , _UpperCamelCase = None      , **_UpperCamelCase      , )      ->							None:






              """simple docstring"""


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

              __snake_case       	=							{} if sp_model_kwargs is None else sp_model_kwargs

              super().__init__(
                  do_lower_case=_UpperCamelCase      , remove_space=_UpperCamelCase      , keep_accents=_UpperCamelCase      , bos_token=_UpperCamelCase      , eos_token=_UpperCamelCase      , unk_token=_UpperCamelCase      , sep_token=_UpperCamelCase      , pad_token=_UpperCamelCase      , cls_token=_UpperCamelCase      , mask_token=_UpperCamelCase      , additional_special_tokens=_UpperCamelCase      , sp_model_kwargs=self.sp_model_kwargs      , **_UpperCamelCase      , )

              __snake_case       	=							3

              __snake_case       	=							do_lower_case
              __snake_case       	=							remove_space
              __snake_case       	=							keep_accents
              __snake_case       	=							vocab_file

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


       @property
       def 			a		(		self   )      ->							str:






              """simple docstring"""


              return len(self.sp_model   )


       def 			a		(		self   )      ->							Union[str, Any]:






              """simple docstring"""


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


       def __getstate__(		self   )      ->							List[str]:






              """simple docstring"""


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


       def __setstate__(		self      , _UpperCamelCase   )      ->							List[str]:






              """simple docstring"""


              __snake_case       	=							d

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

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


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


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

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

              return outputs


       def 			a		(		self      , _UpperCamelCase   )      ->							List[str]:






              """simple docstring"""


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

              return new_pieces


       def 			a		(		self      , _UpperCamelCase   )      ->							Optional[int]:






              """simple docstring"""


              return self.sp_model.PieceToId(_UpperCamelCase   )


       def 			a		(		self      , _UpperCamelCase   )      ->							Optional[int]:






              """simple docstring"""


              return self.sp_model.IdToPiece(_UpperCamelCase   )


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


              __snake_case       	=							"""""".join(_UpperCamelCase   ).replace(_UpperCamelCase      , """ """   ).strip()
              return out_string


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = False      , _UpperCamelCase = None      , _UpperCamelCase = True      , **_UpperCamelCase      , )      ->							str:






              """simple docstring"""


              __snake_case       	=							kwargs.pop("""use_source_tokenizer"""      , _UpperCamelCase   )

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

              # 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
              __snake_case       	=							[]
              __snake_case       	=							[]
              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(_UpperCamelCase   )   )
                                   __snake_case       	=							[]
                            sub_texts.append(_UpperCamelCase   )
                     else:
                            current_sub_text.append(_UpperCamelCase   )
              if current_sub_text:
                     sub_texts.append(self.convert_tokens_to_string(_UpperCamelCase   )   )

              # Mimic the behavior of the Rust tokenizer:
              # By default, there are no spaces between special tokens
              __snake_case       	=							"""""".join(_UpperCamelCase   )

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


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None   )      ->							List[int]:






              """simple docstring"""


              __snake_case       	=							[self.sep_token_id]
              __snake_case       	=							[self.cls_token_id]
              if token_ids_a is None:
                     return token_ids_a + sep + cls
              return token_ids_a + sep + token_ids_a + sep + cls


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None      , _UpperCamelCase = False   )      ->							List[int]:






              """simple docstring"""


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

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


       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None   )      ->							List[int]:






              """simple docstring"""


              __snake_case       	=							[self.sep_token_id]
              __snake_case       	=							[2]

              if token_ids_a is None:
                     return len(token_ids_a + sep   ) * [0] + cls_segment_id
              return len(token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1] + cls_segment_id






       def 			a		(		self      , _UpperCamelCase      , _UpperCamelCase = None   )      ->							Tuple[str]:






              """simple docstring"""


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

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

              return (out_vocab_file,)




from math import isqrt, loga







def 						lowerCamelCase__      ( __A    :int		):


       """simple docstring"""




       __snake_case       	=							[True] * max_number
       for i in range(2	,isqrt(max_number - 1		) + 1		):
              if is_prime[i]:
                     for j in range(i**2	,__A	,__A		):
                            __snake_case       	=							False

       return [i for i in range(2	,__A		) if is_prime[i]]







def 						lowerCamelCase__      ( __A    :int = 8_0_0_8_0_0	,__A    :int = 8_0_0_8_0_0		):


       """simple docstring"""




       __snake_case       	=							degree * loga(__A		)
       __snake_case       	=							int(__A		)
       __snake_case       	=							calculate_prime_numbers(__A		)

       __snake_case       	=							0
       __snake_case       	=							0
       __snake_case       	=							len(__A		) - 1
       while left < right:
              while (
                  prime_numbers[right] * loga(prime_numbers[left]		)
                  + prime_numbers[left] * loga(prime_numbers[right]		)
                  > upper_bound
              ):
                     right -= 1
              hybrid_integers_count += right - left
              left += 1

       return hybrid_integers_count


if __name__ == "__main__":
    print(F'{solution() = }')

