code: 
  '''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  lowerCAmelCase__   (       UpperCamelCase       ):
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
    _UpperCamelCase						= VOCAB_FILES_NAMES
    _UpperCamelCase						= PRETRAINED_VOCAB_FILES_MAP
    _UpperCamelCase						= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _UpperCamelCase						= ['input_ids', 'token_type_ids']
  
    def __init__(self  : str	, lowerCAmelCase_  : Union[str, Any]	, lowerCAmelCase_  : List[Any]=False	, lowerCAmelCase_  : List[str]=True	, lowerCAmelCase_  : Any=True	, lowerCAmelCase_  : Any="<unk>"	, lowerCAmelCase_  : Optional[Any]="[SEP]"	, lowerCAmelCase_  : Optional[int]="<pad>"	, lowerCAmelCase_  : Optional[int]="[CLS]"	, lowerCAmelCase_  : Optional[int]="[MASK]"	, lowerCAmelCase_  : Optional[Dict[str, Any]] = None	, **lowerCAmelCase_  : Union[str, Any]	, )   ->       None:
          # 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.
          snake_case_						       =							(
              AddedToken(lowerCAmelCase_	, lstrip=lowerCAmelCase_	, rstrip=lowerCAmelCase_	, normalized=lowerCAmelCase_    )
              if isinstance(lowerCAmelCase_	, lowerCAmelCase_    )
              else mask_token
          )
  
          snake_case_						       =							{} if sp_model_kwargs is None else sp_model_kwargs
  
          super().__init__(
              do_lower_case=lowerCAmelCase_	, remove_space=lowerCAmelCase_	, keep_accents=lowerCAmelCase_	, unk_token=lowerCAmelCase_	, sep_token=lowerCAmelCase_	, pad_token=lowerCAmelCase_	, cls_token=lowerCAmelCase_	, mask_token=lowerCAmelCase_	, sp_model_kwargs=self.sp_model_kwargs	, **lowerCAmelCase_	, )
  
          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(lowerCAmelCase_    )
  
    @property
    def 		_lowerCamelCase	(self  : List[Any]    )   ->       Tuple:
          return len(self.sp_model    )
  
    def 		_lowerCamelCase	(self  : Union[str, Any]    )   ->       Any:
          snake_case_						       =							{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  : Optional[int]    )   ->       Dict:
          snake_case_						       =							self.__dict__.copy()
          snake_case_						       =							None
          return state
  
    def __setstate__(self  : int	, lowerCAmelCase_  : List[Any]    )   ->       Optional[Any]:
          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 		_lowerCamelCase	(self  : Optional[Any]	, lowerCAmelCase_  : Tuple    )   ->       Tuple:
          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"	, lowerCAmelCase_    )
                snake_case_						       =							"".join([c for c in outputs if not unicodedata.combining(lowerCAmelCase_    )]    )
          if self.do_lower_case:
                snake_case_						       =							outputs.lower()
  
          return outputs
  
    def 		_lowerCamelCase	(self  : str	, lowerCAmelCase_  : str    )   ->       List[str]:
          snake_case_						       =							self.preprocess_text(lowerCAmelCase_    )
          snake_case_						       =							self.sp_model.encode(lowerCAmelCase_	, out_type=lowerCAmelCase_    )
          snake_case_						       =							[]
          for piece in pieces:
                if len(lowerCAmelCase_    ) > 1 and piece[-1] == str(","    ) and piece[-2].isdigit():
                      snake_case_						       =							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:
                                  snake_case_						       =							cur_pieces[1:]
                            else:
                                  snake_case_						       =							cur_pieces[0][1:]
                      cur_pieces.append(piece[-1]    )
                      new_pieces.extend(lowerCAmelCase_    )
                else:
                      new_pieces.append(lowerCAmelCase_    )
  
          return new_pieces
  
    def 		_lowerCamelCase	(self  : Optional[int]	, lowerCAmelCase_  : str    )   ->       str:
          return self.sp_model.PieceToId(lowerCAmelCase_    )
  
    def 		_lowerCamelCase	(self  : Any	, lowerCAmelCase_  : Union[str, Any]    )   ->       Any:
          return self.sp_model.IdToPiece(lowerCAmelCase_    )
  
    def 		_lowerCamelCase	(self  : int	, lowerCAmelCase_  : Dict    )   ->       List[Any]:
          snake_case_						       =							[]
          snake_case_						       =							""
          snake_case_						       =							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
                      snake_case_						       =							True
                      snake_case_						       =							[]
                else:
                      current_sub_tokens.append(lowerCAmelCase_    )
                      snake_case_						       =							False
          out_string += self.sp_model.decode(lowerCAmelCase_    )
          return out_string.strip()
  
    def 		_lowerCamelCase	(self  : Dict	, lowerCAmelCase_  : List[int]	, lowerCAmelCase_  : bool = False	, lowerCAmelCase_  : bool = None	, lowerCAmelCase_  : bool = True	, **lowerCAmelCase_  : Optional[int]	, )   ->       str:
          snake_case_						       =							kwargs.pop("use_source_tokenizer"	, lowerCAmelCase_    )
  
          snake_case_						       =							self.convert_ids_to_tokens(lowerCAmelCase_	, skip_special_tokens=lowerCAmelCase_    )
  
          # 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(lowerCAmelCase_    )    )
                            snake_case_						       =							[]
                      sub_texts.append(lowerCAmelCase_    )
                else:
                      current_sub_text.append(lowerCAmelCase_    )
          if current_sub_text:
                sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase_    )    )
  
          # Mimic the behavior of the Rust tokenizer:
          # No space after <unk>
          if spaces_between_special_tokens:
                snake_case_						       =							re.sub(R"(<unk>) "	, R"\1"	, " ".join(lowerCAmelCase_    )    )
          else:
                snake_case_						       =							"".join(lowerCAmelCase_    )
  
          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(lowerCAmelCase_    )
                return clean_text
          else:
                return text
  
    def 		_lowerCamelCase	(self  : str	, lowerCAmelCase_  : List[int]	, lowerCAmelCase_  : Optional[List[int]] = None    )   ->       List[int]:
          snake_case_						       =							[self.sep_token_id]
          snake_case_						       =							[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 		_lowerCamelCase	(self  : List[str]	, lowerCAmelCase_  : List[int]	, lowerCAmelCase_  : Optional[List[int]] = None	, lowerCAmelCase_  : bool = False    )   ->       List[int]:
  
          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 		_lowerCamelCase	(self  : Tuple	, lowerCAmelCase_  : List[int]	, lowerCAmelCase_  : Optional[List[int]] = None    )   ->       List[int]:
          snake_case_						       =							[self.sep_token_id]
          snake_case_						       =							[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 		_lowerCamelCase	(self  : Tuple	, lowerCAmelCase_  : str	, lowerCAmelCase_  : Optional[str] = None    )   ->       Tuple[str]:
          if not os.path.isdir(lowerCAmelCase_    ):
                logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''    )
                return
          snake_case_						       =							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:
                      snake_case_						       =							self.sp_model.serialized_model_proto()
                      fi.write(lowerCAmelCase_    )
  
          return (out_vocab_file,)
  
  
style_context: 
  '''simple docstring'''
  
  
  
  
  
  from __future__ import annotations
  
  import random
  
  
  
  class  lowerCAmelCase__   :
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
    _UpperCamelCase						= 6
  
    def __init__(self  : List[Any]    )   ->       Optional[Any]:
          snake_case_						       =							list(range(1	, Dice.NUM_SIDES + 1    )    )
  
  
    def 		_lowerCamelCase	(self  : Optional[int]    )   ->       int:
          return random.choice(self.sides    )
  
  def   snake_case_       (							_a     :							int ,					_a     :							int = 2			):
        snake_case_						       =							[Dice() for i in range(_a			)]
        snake_case_						       =							[0] * (len(_a			) * Dice.NUM_SIDES + 1)
        for _ in range(_a			):
              count_of_sum[sum(dice.roll() for dice in dices			)] += 1
        snake_case_						       =							[round((count * 100) / num_throws ,					2			) for count in count_of_sum]
        return probability[num_dice:]  # remove probability of sums that never appear
  
  
  if __name__ == "__main__":
       import doctest
  
       doctest.testmod()
  
  