



'''simple docstring'''





import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE__          =  logging.get_logger(__name__)


SCREAMING_SNAKE_CASE__          =  "▁"

SCREAMING_SNAKE_CASE__          =  {"vocab_file": "spiece.model"}

SCREAMING_SNAKE_CASE__          =  {
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    }
}

SCREAMING_SNAKE_CASE__          =  {
    "google/reformer-crime-and-punishment": 52_4288,
}


class 					snake_case			(UpperCamelCase ):
       lowerCAmelCase__	:Union[str, Any]     =       VOCAB_FILES_NAMES
       lowerCAmelCase__	:Optional[Any]     =       PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__	:Dict     =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__	:int     =       ["input_ids", "attention_mask"]



       def __init__(					self  ,UpperCAmelCase_  ,UpperCAmelCase_="</s>"  ,UpperCAmelCase_="<unk>"  ,UpperCAmelCase_=[]  ,UpperCAmelCase_ = None  ,**UpperCAmelCase_  ,)	->				None:
           lowercase__									=    {} if sp_model_kwargs is None else sp_model_kwargs

           super().__init__(
               eos_token=UpperCAmelCase_  ,unk_token=UpperCAmelCase_  ,additional_special_tokens=UpperCAmelCase_  ,sp_model_kwargs=self.sp_model_kwargs  ,**UpperCAmelCase_  ,)

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



       @property
       def 				_a   (					self   )	->				List[str]:
           return self.sp_model.get_piece_size()



       def 				_a   (					self   )	->				Dict[str, int]:
           lowercase__									=    {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   )	->				int:
           lowercase__									=    self.__dict__.copy()
           lowercase__									=    None
           return state



       def __setstate__(					self  ,UpperCAmelCase_   )	->				Optional[Any]:
           lowercase__									=    d

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

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



       def 				_a   (					self  ,UpperCAmelCase_   )	->				List[str]:
           return self.sp_model.encode(UpperCAmelCase_  ,out_type=UpperCAmelCase_   )



       def 				_a   (					self  ,UpperCAmelCase_   )	->				int:
           return self.sp_model.piece_to_id(UpperCAmelCase_   )



       def 				_a   (					self  ,UpperCAmelCase_   )	->				Optional[Any]:
           if index < self.sp_model.get_piece_size():
               lowercase__									=    self.sp_model.IdToPiece(UpperCAmelCase_   )
           return token



       def 				_a   (					self  ,UpperCAmelCase_   )	->				List[str]:
           lowercase__									=    []
           lowercase__									=    ""
           for token in tokens:
               # make sure that special tokens are not decoded using sentencepiece model
               if token in self.all_special_tokens:
                   out_string += self.sp_model.decode(UpperCAmelCase_   ) + token
                   lowercase__									=    []
               else:
                   current_sub_tokens.append(UpperCAmelCase_   )
           out_string += self.sp_model.decode(UpperCAmelCase_   )
           return out_string.strip()







       def 				_a   (					self  ,UpperCAmelCase_  ,UpperCAmelCase_ = None   )	->				Tuple[str]:
           if not os.path.isdir(UpperCAmelCase_   ):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
               return
           lowercase__									=    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__									=    self.sp_model.serialized_model_proto()
                   fi.write(UpperCAmelCase_   )

           return (out_vocab_file,)









'''simple docstring'''





from __future__ import annotations




def 							lowerCamelCase	(					_snake_case	:    list[int]							):





    '''simple docstring'''


    return len(set(_snake_case							)							) == len(_snake_case							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()




