"""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


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

__A         =				{
    "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",
    },
}

__A         =				{
    "google/fnet-base": 5_1_2,
    "google/fnet-large": 5_1_2,
}

__A         =				"▁"


class 					UpperCAmelCase		(_UpperCAmelCase						):



    """simple docstring"""

    _UpperCAmelCase			:Optional[Any]							=				VOCAB_FILES_NAMES
    _UpperCAmelCase			:List[str]							=				PRETRAINED_VOCAB_FILES_MAP
    _UpperCAmelCase			:Optional[Any]							=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _UpperCAmelCase			:Optional[Any]							=				["input_ids", "token_type_ids"]






    def __init__(     self					,    _UpperCAmelCase					,    _UpperCAmelCase=False					,    _UpperCAmelCase=True					,    _UpperCAmelCase=True					,    _UpperCAmelCase="<unk>"					,    _UpperCAmelCase="[SEP]"					,    _UpperCAmelCase="<pad>"					,    _UpperCAmelCase="[CLS]"					,    _UpperCAmelCase="[MASK]"					,    _UpperCAmelCase = None					,    **_UpperCAmelCase					,    ):
       # 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.
       lowercase__:     Tuple      =   (
           AddedToken(_UpperCAmelCase					,    lstrip=_UpperCAmelCase					,    rstrip=_UpperCAmelCase					,    normalized=_UpperCAmelCase							)
           if isinstance(_UpperCAmelCase					,    _UpperCAmelCase							)
           else mask_token
       )

       lowercase__:     Dict      =   {} if sp_model_kwargs is None else sp_model_kwargs

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

       lowercase__:     str      =   do_lower_case
       lowercase__:     Union[str, Any]      =   remove_space
       lowercase__:     Any      =   keep_accents
       lowercase__:     Optional[Any]      =   vocab_file

       lowercase__:     int      =   spm.SentencePieceProcessor(**self.sp_model_kwargs							)
       self.sp_model.Load(_UpperCAmelCase							)






    @property
    def _snake_case    (     self							):
       return len(self.sp_model							)






    def _snake_case    (     self							):
       lowercase__:     str      =   {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							):
       lowercase__:     Dict      =   self.__dict__.copy()
       lowercase__:     List[str]      =   None
       return state






    def __setstate__(     self					,    _UpperCAmelCase							):
       lowercase__:     int      =   d

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

       lowercase__:     Union[str, Any]      =   spm.SentencePieceProcessor(**self.sp_model_kwargs							)
       self.sp_model.Load(self.vocab_file							)






    def _snake_case    (     self					,    _UpperCAmelCase							):
       if self.remove_space:
          lowercase__:     List[str]      =   ''' '''.join(inputs.strip().split()							)
       else:
          lowercase__:     Tuple      =   inputs
       lowercase__:     List[Any]      =   outputs.replace('''``'''					,    '''"'''							).replace('''\'\''''					,    '''"'''							)

       if not self.keep_accents:
          lowercase__:     Tuple      =   unicodedata.normalize('''NFKD'''					,    _UpperCAmelCase							)
          lowercase__:     List[str]      =   ''''''.join([c for c in outputs if not unicodedata.combining(_UpperCAmelCase							)]							)
       if self.do_lower_case:
          lowercase__:     List[Any]      =   outputs.lower()

       return outputs






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

       return new_pieces






    def _snake_case    (     self					,    _UpperCAmelCase							):
       return self.sp_model.PieceToId(_UpperCAmelCase							)






    def _snake_case    (     self					,    _UpperCAmelCase							):
       return self.sp_model.IdToPiece(_UpperCAmelCase							)






    def _snake_case    (     self					,    _UpperCAmelCase							):
       lowercase__:     str      =   []
       lowercase__:     Dict      =   ''''''
       lowercase__:     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(_UpperCAmelCase							) + token
             lowercase__:     Optional[int]      =   True
             lowercase__:     Optional[int]      =   []
          else:
             current_sub_tokens.append(_UpperCAmelCase							)
             lowercase__:     Tuple      =   False
       out_string += self.sp_model.decode(_UpperCAmelCase							)
       return out_string.strip()






    def _snake_case    (     self					,    _UpperCAmelCase					,    _UpperCAmelCase = False					,    _UpperCAmelCase = None					,    _UpperCAmelCase = True					,    **_UpperCAmelCase					,    ):
       lowercase__:     Union[str, Any]      =   kwargs.pop('''use_source_tokenizer'''					,    _UpperCAmelCase							)

       lowercase__:     Dict      =   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
       lowercase__:     List[Any]      =   []
       lowercase__:     Tuple      =   []
       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							)							)
                lowercase__:     Any      =   []
             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:
       # No space after <unk>
       if spaces_between_special_tokens:
          lowercase__:     Optional[Any]      =   re.sub(r'''(<unk>) '''					,    r'''\1'''					,    ''' '''.join(_UpperCAmelCase							)							)
       else:
          lowercase__:     Optional[Any]      =   ''''''.join(_UpperCAmelCase							)

       lowercase__:     Dict      =   (
           clean_up_tokenization_spaces
           if clean_up_tokenization_spaces is not None
           else self.clean_up_tokenization_spaces
       )
       if clean_up_tokenization_spaces:
          lowercase__:     List[Any]      =   self.clean_up_tokenization(_UpperCAmelCase							)
          return clean_text
       else:
          return text






    def _snake_case    (     self					,    _UpperCAmelCase					,    _UpperCAmelCase = None							):
       lowercase__:     Dict      =   [self.sep_token_id]
       lowercase__:     Union[str, 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 _snake_case    (     self					,    _UpperCAmelCase					,    _UpperCAmelCase = None					,    _UpperCAmelCase = False							):

       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 [1] + ([0] * len(_UpperCAmelCase							)) + [1] + ([0] * len(_UpperCAmelCase							)) + [1]
       return [1] + ([0] * len(_UpperCAmelCase							)) + [1]






    def _snake_case    (     self					,    _UpperCAmelCase					,    _UpperCAmelCase = None							):
       lowercase__:     Dict      =   [self.sep_token_id]
       lowercase__:     Tuple      =   [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 _snake_case    (     self					,    _UpperCAmelCase					,    _UpperCAmelCase = None							):
       if not os.path.isdir(_UpperCAmelCase							):
          logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""							)
          return
       lowercase__:     Optional[int]      =   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:
             lowercase__:     Optional[Any]      =   self.sp_model.serialized_model_proto()
             fi.write(_UpperCAmelCase							)

       return (out_vocab_file,)

"""simple docstring"""






def SCREAMING_SNAKE_CASE__    (     __UpperCAmelCase = 1_0_0_0				)						->						int:
   lowercase__:     Union[str, Any]      =   0
   lowercase__:     Any      =   0
   while 1:
      num += 3
      if num >= n:
         break
      total += num
      num += 2
      if num >= n:
         break
      total += num
      num += 1
      if num >= n:
         break
      total += num
      num += 3
      if num >= n:
         break
      total += num
      num += 1
      if num >= n:
         break
      total += num
      num += 2
      if num >= n:
         break
      total += num
      num += 3
      if num >= n:
         break
      total += num
   return total


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