
"""simple docstring"""






import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging


__SCREAMING_SNAKE_CASE							=     logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE							=     '▁'

__SCREAMING_SNAKE_CASE							=     {
    'vocab_file': 'vocab.json',
    'spm_file': 'sentencepiece.bpe.model',
    'tokenizer_config_file': 'tokenizer_config.json',
}

__SCREAMING_SNAKE_CASE							=     {
    'vocab_file': {
        'facebook/m2m100_418M': 'https://huggingface.co/facebook/m2m100_418M/resolve/main/vocab.json',
        'facebook/m2m100_1.2B': 'https://huggingface.co/facebook/m2m100_1.2B/resolve/main/vocab.json',
    },
    'spm_file': {
        'facebook/m2m100_418M': 'https://huggingface.co/facebook/m2m100_418M/resolve/main/sentencepiece.bpe.model',
        'facebook/m2m100_1.2B': 'https://huggingface.co/facebook/m2m100_1.2B/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_config_file': {
        'facebook/m2m100_418M': 'https://huggingface.co/facebook/m2m100_418M/resolve/main/tokenizer_config.json',
        'facebook/m2m100_1.2B': 'https://huggingface.co/facebook/m2m100_1.2B/resolve/main/tokenizer_config.json',
    },
}

__SCREAMING_SNAKE_CASE							=     {
    'facebook/m2m100_418M': 1_024,
}

# fmt: off
__SCREAMING_SNAKE_CASE							=     {
    'm2m100': ['af', 'am', 'ar', 'ast', 'az', 'ba', 'be', 'bg', 'bn', 'br', 'bs', 'ca', 'ceb', 'cs', 'cy', 'da', 'de', 'el', 'en', 'es', 'et', 'fa', 'ff', 'fi', 'fr', 'fy', 'ga', 'gd', 'gl', 'gu', 'ha', 'he', 'hi', 'hr', 'ht', 'hu', 'hy', 'id', 'ig', 'ilo', 'is', 'it', 'ja', 'jv', 'ka', 'kk', 'km', 'kn', 'ko', 'lb', 'lg', 'ln', 'lo', 'lt', 'lv', 'mg', 'mk', 'ml', 'mn', 'mr', 'ms', 'my', 'ne', 'nl', 'no', 'ns', 'oc', 'or', 'pa', 'pl', 'ps', 'pt', 'ro', 'ru', 'sd', 'si', 'sk', 'sl', 'so', 'sq', 'sr', 'ss', 'su', 'sv', 'sw', 'ta', 'th', 'tl', 'tn', 'tr', 'uk', 'ur', 'uz', 'vi', 'wo', 'xh', 'yi', 'yo', 'zh', 'zu'],
    'wmt21': ['en', 'ha', 'is', 'ja', 'cs', 'ru', 'zh', 'de']
}





class 				a__					(						A__       ):
     UpperCAmelCase__         =      VOCAB_FILES_NAMES
     UpperCAmelCase__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__         =      PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__         =      ['''input_ids''', '''attention_mask''']

     UpperCAmelCase__         =      []
     UpperCAmelCase__         =      []



     def __init__(							self :Optional[int]      ,  _lowerCamelCase :List[str]      ,  _lowerCamelCase :Any      ,  _lowerCamelCase :Optional[Any]=None      ,  _lowerCamelCase :Union[str, Any]=None      ,  _lowerCamelCase :Optional[Any]="<s>"      ,  _lowerCamelCase :Optional[Any]="</s>"      ,  _lowerCamelCase :Any="</s>"      ,  _lowerCamelCase :Optional[Any]="<pad>"      ,  _lowerCamelCase :Tuple="<unk>"      ,  _lowerCamelCase :Union[str, Any]="m2m100"      ,  _lowerCamelCase :Optional[Dict[str, Any]] = None      ,  _lowerCamelCase :List[str]=8      ,  **_lowerCamelCase :List[Any]      ,  ):







      '''simple docstring'''



      UpperCamelCase_     :					Any   	={} if sp_model_kwargs is None else sp_model_kwargs

      UpperCamelCase_     :					Union[str, Any]   	=language_codes
      UpperCamelCase_     :					List[Any]   	=FAIRSEQ_LANGUAGE_CODES[language_codes]
      UpperCamelCase_     :					Optional[int]   	={lang_code: f'''__{lang_code}__''' for lang_code in fairseq_language_code}

      UpperCamelCase_     :					Tuple   	=kwargs.get('additional_special_tokens'      ,  []   )
      kwargs["additional_special_tokens"] += [
          self.get_lang_token(_lowerCamelCase   )
          for lang_code in fairseq_language_code
          if self.get_lang_token(_lowerCamelCase   ) not in kwargs["additional_special_tokens"]
      ]

      super().__init__(
          src_lang=_lowerCamelCase      ,  tgt_lang=_lowerCamelCase      ,  bos_token=_lowerCamelCase      ,  eos_token=_lowerCamelCase      ,  sep_token=_lowerCamelCase      ,  unk_token=_lowerCamelCase      ,  pad_token=_lowerCamelCase      ,  language_codes=_lowerCamelCase      ,  sp_model_kwargs=self.sp_model_kwargs      ,  num_madeup_words=_lowerCamelCase      ,  **_lowerCamelCase      ,  )

      UpperCamelCase_     :					Union[str, Any]   	=vocab_file
      UpperCamelCase_     :					Dict   	=load_json(_lowerCamelCase   )
      UpperCamelCase_     :					Tuple   	={v: k for k, v in self.encoder.items()}
      UpperCamelCase_     :					List[Any]   	=spm_file
      UpperCamelCase_     :					Any   	=load_spm(_lowerCamelCase      ,  self.sp_model_kwargs   )

      UpperCamelCase_     :					Union[str, Any]   	=len(self.encoder   )

      UpperCamelCase_     :					Union[str, Any]   	={
          self.get_lang_token(_lowerCamelCase   ): self.encoder_size + i for i, lang_code in enumerate(_lowerCamelCase   )
      }
      UpperCamelCase_     :					Optional[Any]   	={lang_code: self.encoder_size + i for i, lang_code in enumerate(_lowerCamelCase   )}
      UpperCamelCase_     :					str   	={v: k for k, v in self.lang_token_to_id.items()}

      UpperCamelCase_     :					Optional[int]   	=src_lang if src_lang is not None else 'en'
      UpperCamelCase_     :					str   	=tgt_lang
      UpperCamelCase_     :					int   	=self.get_lang_id(self._src_lang   )
      self.set_src_lang_special_tokens(self._src_lang   )

      UpperCamelCase_     :					Optional[Any]   	=num_madeup_words



     @property
     def  lowerCamelCase_						(							self :Any   ):







      '''simple docstring'''



      return len(self.encoder   ) + len(self.lang_token_to_id   )



     @property
     def  lowerCamelCase_						(							self :Optional[int]   ):







      '''simple docstring'''



      return self._src_lang



     @src_lang.setter
     def  lowerCamelCase_						(							self :Optional[int]      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	=new_src_lang
      self.set_src_lang_special_tokens(self._src_lang   )



     def  lowerCamelCase_						(							self :Optional[int]      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



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



     def  lowerCamelCase_						(							self :List[Any]      ,  _lowerCamelCase :Tuple   ):







      '''simple docstring'''



      if token in self.lang_token_to_id:
       return self.lang_token_to_id[token]
      return self.encoder.get(_lowerCamelCase      ,  self.encoder[self.unk_token]   )



     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :int   ):







      '''simple docstring'''



      if index in self.id_to_lang_token:
       return self.id_to_lang_token[index]
      return self.decoder.get(_lowerCamelCase      ,  self.unk_token   )



     def  lowerCamelCase_						(							self :Tuple      ,  _lowerCamelCase :int   ):







      '''simple docstring'''



      UpperCamelCase_     :					Optional[int]   	=[]
      UpperCamelCase_     :					str   	=''
      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(_lowerCamelCase   ) + token
        UpperCamelCase_     :					Optional[int]   	=[]
       else:
        current_sub_tokens.append(_lowerCamelCase   )
      out_string += self.sp_model.decode(_lowerCamelCase   )
      return out_string.strip()



     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None      ,  _lowerCamelCase :bool = False   ):







      '''simple docstring'''



      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=_lowerCamelCase      ,  token_ids_a=_lowerCamelCase      ,  already_has_special_tokens=_lowerCamelCase   )

      UpperCamelCase_     :					Dict   	=[1] * len(self.prefix_tokens   )
      UpperCamelCase_     :					int   	=[1] * len(self.suffix_tokens   )
      if token_ids_a is None:
       return prefix_ones + ([0] * len(_lowerCamelCase   )) + suffix_ones
      return prefix_ones + ([0] * len(_lowerCamelCase   )) + ([0] * len(_lowerCamelCase   )) + suffix_ones



     def  lowerCamelCase_						(							self :List[str]      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None   ):







      '''simple docstring'''



      if token_ids_a is None:
       return self.prefix_tokens + token_ids_a + self.suffix_tokens
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens



     def  lowerCamelCase_						(							self :Union[str, Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Union[str, Any]   	={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 :List[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Dict   	=self.__dict__.copy()
      UpperCamelCase_     :					Dict   	=None
      return state



     def __setstate__(							self :Tuple      ,  _lowerCamelCase :Dict   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[str]   	=d

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

      UpperCamelCase_     :					Union[str, Any]   	=load_spm(self.spm_file      ,  self.sp_model_kwargs   )



     def  lowerCamelCase_						(							self :List[Any]      ,  _lowerCamelCase :str      ,  _lowerCamelCase :Optional[str] = None   ):







      '''simple docstring'''



      UpperCamelCase_     :					Any   	=Path(_lowerCamelCase   )
      if not save_dir.is_dir():
       raise OSError(f'''{save_directory} should be a directory'''   )
      UpperCamelCase_     :					Union[str, Any]   	=save_dir / (
          (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['vocab_file']
      )
      UpperCamelCase_     :					Optional[Any]   	=save_dir / (
          (filename_prefix + '-' if filename_prefix else '') + self.vocab_files_names['spm_file']
      )

      save_json(self.encoder      ,  _lowerCamelCase   )

      if os.path.abspath(self.spm_file   ) != os.path.abspath(_lowerCamelCase   ) and os.path.isfile(self.spm_file   ):
       copyfile(self.spm_file      ,  _lowerCamelCase   )
      elif not os.path.isfile(self.spm_file   ):
       with open(_lowerCamelCase      ,  'wb'   ) as fi:
        UpperCamelCase_     :					Any   	=self.sp_model.serialized_model_proto()
        fi.write(_lowerCamelCase   )

      return (str(_lowerCamelCase   ), str(_lowerCamelCase   ))



     def  lowerCamelCase_						(							self :int      ,  _lowerCamelCase :List[str]      ,  _lowerCamelCase :str = "en"      ,  _lowerCamelCase :Optional[List[str]] = None      ,  _lowerCamelCase :str = "ro"      ,  **_lowerCamelCase :Union[str, Any]      ,  ):







      '''simple docstring'''



      UpperCamelCase_     :					Dict   	=src_lang
      UpperCamelCase_     :					Optional[Any]   	=tgt_lang
      self.set_src_lang_special_tokens(self.src_lang   )
      return super().prepare_seqaseq_batch(_lowerCamelCase      ,  _lowerCamelCase      ,  **_lowerCamelCase   )



     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :Union[str, Any]      ,  _lowerCamelCase :Optional[str]      ,  _lowerCamelCase :Optional[str]      ,  **_lowerCamelCase :int   ):







      '''simple docstring'''



      if src_lang is None or tgt_lang is None:
       raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'   )
      UpperCamelCase_     :					Any   	=src_lang
      UpperCamelCase_     :					Tuple   	=self(_lowerCamelCase      ,  add_special_tokens=_lowerCamelCase      ,  **_lowerCamelCase   )
      UpperCamelCase_     :					Union[str, Any]   	=self.get_lang_id(_lowerCamelCase   )
      UpperCamelCase_     :					Dict   	=tgt_lang_id
      return inputs



     def  lowerCamelCase_						(							self :str   ):







      '''simple docstring'''



      self.set_src_lang_special_tokens(self.src_lang   )



     def  lowerCamelCase_						(							self :str   ):







      '''simple docstring'''



      self.set_tgt_lang_special_tokens(self.tgt_lang   )



     def  lowerCamelCase_						(							self :Any      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	=self.get_lang_token(_lowerCamelCase   )
      UpperCamelCase_     :					List[str]   	=self.lang_token_to_id[lang_token]
      UpperCamelCase_     :					Tuple   	=[self.cur_lang_id]
      UpperCamelCase_     :					List[Any]   	=[self.eos_token_id]



     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      UpperCamelCase_     :					Any   	=self.get_lang_token(_lowerCamelCase   )
      UpperCamelCase_     :					Dict   	=self.lang_token_to_id[lang_token]
      UpperCamelCase_     :					Dict   	=[self.cur_lang_id]
      UpperCamelCase_     :					Optional[int]   	=[self.eos_token_id]



     def  lowerCamelCase_						(							self :Any      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      return self.lang_code_to_token[lang]




     def  lowerCamelCase_						(							self :List[str]      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      UpperCamelCase_     :					Optional[Any]   	=self.get_lang_token(_lowerCamelCase   )
      return self.lang_token_to_id[lang_token]




def       A_  (				__lowercase						,	__lowercase	):
 UpperCamelCase_     :					Any   	=sentencepiece.SentencePieceProcessor(**__lowercase	)
 spm.Load(str(__lowercase	)	)
 return spm




def       A_  (				__lowercase	):
 with open(__lowercase						,	'r'	) as f:
  return json.load(__lowercase	)





def       A_  (				__lowercase						,	__lowercase	):
 with open(__lowercase						,	'w'	) as f:
  json.dump(__lowercase						,	__lowercase						,	indent=2	)


"""simple docstring"""






import os
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


__SCREAMING_SNAKE_CASE							=     logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE							=     {'vocab_file': 'spiece.model'}

__SCREAMING_SNAKE_CASE							=     {
    'vocab_file': {
        'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/spiece.model',
        'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/spiece.model',
        'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model',
        'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model',
        'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/spiece.model',
        'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/spiece.model',
        'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model',
        'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model',
    }
}

__SCREAMING_SNAKE_CASE							=     {
    'albert-base-v1': 512,
    'albert-large-v1': 512,
    'albert-xlarge-v1': 512,
    'albert-xxlarge-v1': 512,
    'albert-base-v2': 512,
    'albert-large-v2': 512,
    'albert-xlarge-v2': 512,
    'albert-xxlarge-v2': 512,
}

__SCREAMING_SNAKE_CASE							=     '▁'





class 				a__					(						A__       ):
     UpperCAmelCase__         =      VOCAB_FILES_NAMES
     UpperCAmelCase__         =      PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



     def __init__(							self :Optional[Any]      ,  _lowerCamelCase :int      ,  _lowerCamelCase :List[Any]=True      ,  _lowerCamelCase :int=True      ,  _lowerCamelCase :Tuple=False      ,  _lowerCamelCase :Optional[Any]="[CLS]"      ,  _lowerCamelCase :List[Any]="[SEP]"      ,  _lowerCamelCase :Dict="<unk>"      ,  _lowerCamelCase :int="[SEP]"      ,  _lowerCamelCase :int="<pad>"      ,  _lowerCamelCase :Optional[Any]="[CLS]"      ,  _lowerCamelCase :str="[MASK]"      ,  _lowerCamelCase :Optional[Dict[str, Any]] = None      ,  **_lowerCamelCase :Union[str, Any]      ,  ):







      '''simple docstring'''



      UpperCamelCase_     :					Union[str, Any]   	=(
          AddedToken(_lowerCamelCase      ,  lstrip=_lowerCamelCase      ,  rstrip=_lowerCamelCase      ,  normalized=_lowerCamelCase   )
          if isinstance(_lowerCamelCase      ,  _lowerCamelCase   )
          else mask_token
      )

      UpperCamelCase_     :					Any   	={} if sp_model_kwargs is None else sp_model_kwargs

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

      UpperCamelCase_     :					str   	=do_lower_case
      UpperCamelCase_     :					Any   	=remove_space
      UpperCamelCase_     :					List[Any]   	=keep_accents
      UpperCamelCase_     :					Optional[Any]   	=vocab_file

      UpperCamelCase_     :					List[str]   	=spm.SentencePieceProcessor(**self.sp_model_kwargs   )
      self.sp_model.Load(_lowerCamelCase   )



     @property
     def  lowerCamelCase_						(							self :List[str]   ):







      '''simple docstring'''



      return len(self.sp_model   )



     def  lowerCamelCase_						(							self :Optional[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Optional[int]   	={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]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Optional[Any]   	=self.__dict__.copy()
      UpperCamelCase_     :					Optional[Any]   	=None
      return state



     def __setstate__(							self :List[Any]      ,  _lowerCamelCase :Any   ):







      '''simple docstring'''



      UpperCamelCase_     :					Union[str, Any]   	=d

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

      UpperCamelCase_     :					List[Any]   	=spm.SentencePieceProcessor(**self.sp_model_kwargs   )
      self.sp_model.Load(self.vocab_file   )



     def  lowerCamelCase_						(							self :Union[str, Any]      ,  _lowerCamelCase :Tuple   ):







      '''simple docstring'''



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

      if not self.keep_accents:
       UpperCamelCase_     :					Optional[Any]   	=unicodedata.normalize('NFKD'      ,  _lowerCamelCase   )
       UpperCamelCase_     :					Tuple   	=''.join([c for c in outputs if not unicodedata.combining(_lowerCamelCase   )]   )
      if self.do_lower_case:
       UpperCamelCase_     :					Optional[Any]   	=outputs.lower()

      return outputs



     def  lowerCamelCase_						(							self :Dict      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



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

      return new_pieces



     def  lowerCamelCase_						(							self :Dict      ,  _lowerCamelCase :List[str]   ):







      '''simple docstring'''



      return self.sp_model.PieceToId(_lowerCamelCase   )



     def  lowerCamelCase_						(							self :Optional[Any]      ,  _lowerCamelCase :Union[str, Any]   ):







      '''simple docstring'''



      return self.sp_model.IdToPiece(_lowerCamelCase   )



     def  lowerCamelCase_						(							self :Union[str, Any]      ,  _lowerCamelCase :Optional[int]   ):







      '''simple docstring'''



      UpperCamelCase_     :					int   	=[]
      UpperCamelCase_     :					int   	=''
      UpperCamelCase_     :					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(_lowerCamelCase   ) + token
        UpperCamelCase_     :					List[Any]   	=True
        UpperCamelCase_     :					str   	=[]
       else:
        current_sub_tokens.append(_lowerCamelCase   )
        UpperCamelCase_     :					List[Any]   	=False
      out_string += self.sp_model.decode(_lowerCamelCase   )
      return out_string.strip()



     def  lowerCamelCase_						(							self :Optional[int]      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None   ):







      '''simple docstring'''



      UpperCamelCase_     :					Tuple   	=[self.sep_token_id]
      UpperCamelCase_     :					Tuple   	=[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 :Union[str, Any]      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None      ,  _lowerCamelCase :bool = False   ):







      '''simple docstring'''



      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 :List[Any]      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None   ):







      '''simple docstring'''



      UpperCamelCase_     :					Tuple   	=[self.sep_token_id]
      UpperCamelCase_     :					List[str]   	=[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   ):







      '''simple docstring'''



      if not os.path.isdir(_lowerCamelCase   ):
       logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''   )
       return
      UpperCamelCase_     :					int   	=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:
        UpperCamelCase_     :					Dict   	=self.sp_model.serialized_model_proto()
        fi.write(_lowerCamelCase   )

      return (out_vocab_file,)
