



'''simple docstring'''





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


_UpperCamelCase							       =		logging.get_logger(__name__)
_UpperCamelCase							       =		{"""vocab_file""": """spiece.model"""}

_UpperCamelCase							       =		{
    """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""",
    },
}

_UpperCamelCase							       =		{
    """google/fnet-base""": 512,
    """google/fnet-large""": 512,
}

_UpperCamelCase							       =		"""▁"""






class       lowerCamelCase_					(       a__  ):
  """simple docstring"""




  a_							      =VOCAB_FILES_NAMES
  a_							      =PRETRAINED_VOCAB_FILES_MAP
  a_							      =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a_							      =["""input_ids""", """token_type_ids"""]




  def __init__(				self   :			Union[str, Any]    ,			_a   :			Optional[int]    ,			_a   :			Any=False    ,			_a   :			Any=True    ,			_a   :			Optional[Any]=True    ,			_a   :			List[Any]="<unk>"    ,			_a   :			Any="[SEP]"    ,			_a   :			List[Any]="<pad>"    ,			_a   :			List[Any]="[CLS]"    ,			_a   :			Union[str, Any]="[MASK]"    ,			_a   :			List[Any] = None    ,			**_a   :			Any    ,			)      ->      None:
    __lowerCamelCase : Dict					 =				(
        AddedToken(__A    ,			lstrip=__A    ,			rstrip=__A    ,			normalized=__A     )
        if isinstance(__A    ,			__A     )
        else mask_token
    )

    __lowerCamelCase : List[Any]					 =				{} 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    ,			)

    __lowerCamelCase : Optional[int]					 =				do_lower_case
    __lowerCamelCase : str					 =				remove_space
    __lowerCamelCase : int					 =				keep_accents
    __lowerCamelCase : Tuple					 =				vocab_file

    __lowerCamelCase : Tuple					 =				spm.SentencePieceProcessor(**self.sp_model_kwargs     )
    self.sp_model.Load(__A     )




  @property
  def 		_lowercase  (				self   :			Dict     )      ->      int:
    return len(self.sp_model     )




  def 		_lowercase  (				self   :			Tuple     )      ->      int:
    __lowerCamelCase : Dict					 =				{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   :			Any     )      ->      Optional[Any]:
    __lowerCamelCase : int					 =				self.__dict__.copy()
    __lowerCamelCase : int					 =				None
    return state




  def __setstate__(				self   :			Tuple    ,			_a   :			Tuple     )      ->      Dict:
    __lowerCamelCase : int					 =				d

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

    __lowerCamelCase : Tuple					 =				spm.SentencePieceProcessor(**self.sp_model_kwargs     )
    self.sp_model.Load(self.vocab_file     )




  def 		_lowercase  (				self   :			Optional[int]    ,			_a   :			Optional[Any]     )      ->      int:







    if self.remove_space:
      __lowerCamelCase : Optional[Any]					 =				" ".join(inputs.strip().split()     )
    else:
      __lowerCamelCase : Tuple					 =				inputs
    __lowerCamelCase : List[Any]					 =				outputs.replace('``'    ,			'\"'     ).replace('\'\''    ,			'\"'     )

    if not self.keep_accents:
      __lowerCamelCase : str					 =				unicodedata.normalize('NFKD'    ,			__A     )
      __lowerCamelCase : str					 =				"".join([c for c in outputs if not unicodedata.combining(__A     )]     )
    if self.do_lower_case:
      __lowerCamelCase : int					 =				outputs.lower()

    return outputs




  def 		_lowercase  (				self   :			Dict    ,			_a   :			str     )      ->      List[str]:
    __lowerCamelCase : List[Any]					 =				self.preprocess_text(__A     )
    __lowerCamelCase : int					 =				self.sp_model.encode(__A    ,			out_type=__A     )
    __lowerCamelCase : Union[str, Any]					 =				[]
    for piece in pieces:
      if len(__A     ) > 1 and piece[-1] == str(','     ) and piece[-2].isdigit():
        __lowerCamelCase : int					 =				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:
            __lowerCamelCase : List[str]					 =				cur_pieces[1:]
          else:
            __lowerCamelCase : Any					 =				cur_pieces[0][1:]
        cur_pieces.append(piece[-1]     )
        new_pieces.extend(__A     )
      else:
        new_pieces.append(__A     )

    return new_pieces




  def 		_lowercase  (				self   :			Dict    ,			_a   :			str     )      ->      Dict:
    return self.sp_model.PieceToId(__A     )




  def 		_lowercase  (				self   :			str    ,			_a   :			int     )      ->      Optional[Any]:
    return self.sp_model.IdToPiece(__A     )




  def 		_lowercase  (				self   :			Optional[int]    ,			_a   :			Union[str, Any]     )      ->      Optional[Any]:
    __lowerCamelCase : Any					 =				[]
    __lowerCamelCase : Union[str, Any]					 =				""
    __lowerCamelCase : int					 =				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
        __lowerCamelCase : Tuple					 =				True
        __lowerCamelCase : str					 =				[]
      else:
        current_sub_tokens.append(__A     )
        __lowerCamelCase : List[str]					 =				False
    out_string += self.sp_model.decode(__A     )
    return out_string.strip()




  def 		_lowercase  (				self   :			Any    ,			_a   :			List[str]    ,			_a   :			Tuple = False    ,			_a   :			Optional[int] = None    ,			_a   :			Optional[Any] = True    ,			**_a   :			Dict    ,			)      ->      str:
    __lowerCamelCase : Dict					 =				kwargs.pop('use_source_tokenizer'    ,			__A     )

    __lowerCamelCase : int					 =				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
    __lowerCamelCase : int					 =				[]
    __lowerCamelCase : Optional[int]					 =				[]
    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     )     )
          __lowerCamelCase : List[str]					 =				[]
        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:
      __lowerCamelCase : Optional[int]					 =				re.sub(R'(<unk>) '    ,			R'\1'    ,			' '.join(__A     )     )
    else:
      __lowerCamelCase : Optional[Any]					 =				"".join(__A     )

    __lowerCamelCase : int					 =				(
        clean_up_tokenization_spaces
        if clean_up_tokenization_spaces is not None
        else self.clean_up_tokenization_spaces
    )
    if clean_up_tokenization_spaces:
      __lowerCamelCase : Tuple					 =				self.clean_up_tokenization(__A     )
      return clean_text
    else:
      return text




  def 		_lowercase  (				self   :			Optional[Any]    ,			_a   :			int    ,			_a   :			Optional[Any] = None     )      ->      List[int]:
    __lowerCamelCase : str					 =				[self.sep_token_id]
    __lowerCamelCase : int					 =				[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 		_lowercase  (				self   :			Optional[int]    ,			_a   :			List[Any]    ,			_a   :			int = None    ,			_a   :			Any = False     )      ->      List[int]:







    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 		_lowercase  (				self   :			str    ,			_a   :			str    ,			_a   :			Dict = None     )      ->      List[int]:
    __lowerCamelCase : Tuple					 =				[self.sep_token_id]
    __lowerCamelCase : Optional[int]					 =				[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 		_lowercase  (				self   :			Optional[int]    ,			_a   :			str    ,			_a   :			Tuple = None     )      ->      Tuple[str]:







    if not os.path.isdir(__A     ):
      logger.error(f'Vocabulary path ({save_directory}) should be a directory'     )
      return
    __lowerCamelCase : Optional[Any]					 =				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:
        __lowerCamelCase : Tuple					 =				self.sp_model.serialized_model_proto()
        fi.write(__A     )

    return (out_vocab_file,)











'''simple docstring'''





def  a_  (							_lowerCAmelCase = 1000 )   ->   int:
  return sum(i for i in range(_lowerCAmelCase ) if i % 3 == 0 or i % 5 == 0 )


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






