




'''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


lowerCAmelCase_      :  List[Any]				     =  logging.get_logger(__name__)


lowerCAmelCase_      :  int				     =  '▁'

lowerCAmelCase_      :  Optional[int]				     =  {'vocab_file': 'spiece.model'}

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

lowerCAmelCase_      :  Dict				     =  {
    'google/reformer-crime-and-punishment': 52_4288,
}







class      SCREAMING_SNAKE_CASE    (						snake_case_				):
      __magic_name__  :       Union[str, Any]   							=					VOCAB_FILES_NAMES
      __magic_name__  :       Union[str, Any]   							=					PRETRAINED_VOCAB_FILES_MAP
      __magic_name__  :       List[str]   							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __magic_name__  :       Union[str, Any]   							=					['''input_ids''', '''attention_mask''']






      def __init__( self   :  List[str]						,						lowercase__   :  Any						,						lowercase__   :  Optional[Any]="</s>"						,						lowercase__   :  Optional[int]="<unk>"						,						lowercase__   :  Optional[int]=[]						,						lowercase__   :  Optional[Dict[str, Any]] = None						,						**lowercase__   :  str						,						):


           '''simple docstring'''

           a_     :							Optional[Any]     						=  {} if sp_model_kwargs is None else sp_model_kwargs

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

           a_     :							str     						=  vocab_file
           a_     :							List[str]     						=  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
           self.sp_model.Load(lowercase__       )






      @property
      def 							lowercase_						( self   :  Optional[Any]       ):


           '''simple docstring'''

           return self.sp_model.get_piece_size()






      def 							lowercase_						( self   :  str       ):


           '''simple docstring'''

           a_     :							int     						=  {self.convert_ids_to_tokens(lowercase__       ): i for i in range(self.vocab_size       )}
           vocab.update(self.added_tokens_encoder       )
           return vocab






      def __getstate__( self   :  Dict       ):


           '''simple docstring'''

           a_     :							str     						=  self.__dict__.copy()
           a_     :							Tuple     						=  None
           return state






      def __setstate__( self   :  List[Any]						,						lowercase__   :  Optional[int]       ):


           '''simple docstring'''

           a_     :							Optional[Any]     						=  d

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

           a_     :							Any     						=  spm.SentencePieceProcessor(**self.sp_model_kwargs       )
           self.sp_model.Load(self.vocab_file       )






      def 							lowercase_						( self   :  List[str]						,						lowercase__   :  str       ):


           '''simple docstring'''

           return self.sp_model.encode(lowercase__						,						out_type=lowercase__       )






      def 							lowercase_						( self   :  List[str]						,						lowercase__   :  Any       ):


           '''simple docstring'''

           return self.sp_model.piece_to_id(lowercase__       )






      def 							lowercase_						( self   :  Dict						,						lowercase__   :  Dict       ):


           '''simple docstring'''

           if index < self.sp_model.get_piece_size():
                a_     :							int     						=  self.sp_model.IdToPiece(lowercase__       )
           return token






      def 							lowercase_						( self   :  Any						,						lowercase__   :  Dict       ):


           '''simple docstring'''

           a_     :							Tuple     						=  []
           a_     :							List[Any]     						=  """"""
           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(lowercase__       ) + token
                     a_     :							Optional[int]     						=  []
                else:
                     current_sub_tokens.append(lowercase__       )
           out_string += self.sp_model.decode(lowercase__       )
           return out_string.strip()






      def 							lowercase_						( self   :  str						,						lowercase__   :  str						,						lowercase__   :  Optional[str] = None       ):


           '''simple docstring'''

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

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

           return (out_vocab_file,)






'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


lowerCAmelCase_      :  Optional[Any]				     =  {}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase_      :  Any				     =  ['GPTSw3Tokenizer']


if TYPE_CHECKING:
 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_gpt_swa import GPTSwaTokenizer

else:
 import sys

 lowerCAmelCase_      :  int				     =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
