




"""simple docstring"""


import os
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''': '''sentencepiece.bpe.model'''}

A_						=				{
    '''vocab_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'''
        ),
    },
}

A_						=				{
    '''moussaKam/mbarthez''': 10_24,
    '''moussaKam/barthez''': 10_24,
    '''moussaKam/barthez-orangesum-title''': 10_24,
}

A_						=				'''▁'''






class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					VOCAB_FILES_NAMES
 lowercase__ 					=					PRETRAINED_VOCAB_FILES_MAP
 lowercase__ 					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase__ 					=					["input_ids", "attention_mask"]


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




   '''simple docstring'''



   _snake_case							:		int								=  AddedToken(a_,      lstrip=a_,      rstrip=a_		) if isinstance(a_,      a_		) else mask_token

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

   super().__init__(
       bos_token=a_,      eos_token=a_,      unk_token=a_,      sep_token=a_,      cls_token=a_,      pad_token=a_,      mask_token=a_,      sp_model_kwargs=self.sp_model_kwargs,      **a_,      )

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

   _snake_case							:		Optional[Any]								=  {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

   _snake_case							:		Union[str, Any]								=  len(self.sp_model		) - 1
   _snake_case							:		Tuple								=  {v: k for k, v in self.fairseq_tokens_to_ids.items()}


 def  UpperCamelCase_   (				self:		Optional[Any],      a_:		List[int],      a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   if token_ids_a is None:
     return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
   _snake_case							:		str								=  [self.cls_token_id]
   _snake_case							:		List[Any]								=  [self.sep_token_id]
   return cls + token_ids_a + sep + sep + token_ids_a + sep


 def  UpperCamelCase_   (				self:		List[Any],      a_:		List[int],      a_:		Optional[List[int]] = None,      a_:		bool = False		):




   '''simple docstring'''



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

   if token_ids_a is None:
     return [1] + ([0] * len(a_		)) + [1]
   return [1] + ([0] * len(a_		)) + [1, 1] + ([0] * len(a_		)) + [1]


 def  UpperCamelCase_   (				self:		str,      a_:		List[int],      a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   _snake_case							:		Union[str, Any]								=  [self.sep_token_id]
   _snake_case							:		int								=  [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 + sep + token_ids_a + sep		) * [0]


 @property
 def  UpperCamelCase_   (				self:		int		):




   '''simple docstring'''



   return len(self.sp_model		)


 def  UpperCamelCase_   (				self:		Optional[Any]		):




   '''simple docstring'''



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


 def  UpperCamelCase_   (				self:		Dict,      a_:		str		):




   '''simple docstring'''



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


 def  UpperCamelCase_   (				self:		Union[str, Any],      a_:		Union[str, Any]		):




   '''simple docstring'''



   if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
   _snake_case							:		Optional[int]								=  self.sp_model.PieceToId(a_		)

   return spm_id if spm_id else self.unk_token_id


 def  UpperCamelCase_   (				self:		Tuple,      a_:		Tuple		):




   '''simple docstring'''



   if index in self.fairseq_ids_to_tokens:
     return self.fairseq_ids_to_tokens[index]
   return self.sp_model.IdToPiece(a_		)


 def  UpperCamelCase_   (				self:		Optional[int],      a_:		int		):




   '''simple docstring'''



   _snake_case							:		List[Any]								=  []
   _snake_case							:		Dict								=  """"""
   _snake_case							:		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(a_		) + token
       _snake_case							:		Optional[int]								=  True
       _snake_case							:		str								=  []
     else:
       current_sub_tokens.append(a_		)
       _snake_case							:		List[str]								=  False
   out_string += self.sp_model.decode(a_		)
   return out_string.strip()


 def __getstate__(				self:		int		):




   '''simple docstring'''



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


 def __setstate__(				self:		Optional[int],      a_:		Union[str, Any]		):




   '''simple docstring'''



   _snake_case							:		Optional[Any]								=  d

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

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


 def  UpperCamelCase_   (				self:		Optional[Any],      a_:		str,      a_:		Optional[str] = None		):




   '''simple docstring'''



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

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

   return (out_vocab_file,)








"""simple docstring"""


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


A_						=				logging.get_logger(__name__)

A_						=				{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

A_						=				{
    '''vocab_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

A_						=				{
    '''yjernite/retribert-base-uncased''': 5_12,
}


A_						=				{
    '''yjernite/retribert-base-uncased''': {'''do_lower_case''': True},
}






class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					VOCAB_FILES_NAMES
 lowercase__ 					=					PRETRAINED_VOCAB_FILES_MAP
 lowercase__ 					=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase__ 					=					PRETRAINED_INIT_CONFIGURATION
 lowercase__ 					=					RetriBertTokenizer
 lowercase__ 					=					["input_ids", "attention_mask"]


 def __init__(				self:		int,      a_:		int=None,      a_:		Dict=None,      a_:		Any=True,      a_:		int="[UNK]",      a_:		Any="[SEP]",      a_:		List[Any]="[PAD]",      a_:		List[Any]="[CLS]",      a_:		str="[MASK]",      a_:		Dict=True,      a_:		Optional[int]=None,      **a_:		Tuple,      ):




   '''simple docstring'''



   super().__init__(
       a_,      tokenizer_file=a_,      do_lower_case=a_,      unk_token=a_,      sep_token=a_,      pad_token=a_,      cls_token=a_,      mask_token=a_,      tokenize_chinese_chars=a_,      strip_accents=a_,      **a_,      )

   _snake_case							:		List[Any]								=  json.loads(self.backend_tokenizer.normalizer.__getstate__()		)
   if (
       normalizer_state.get("""lowercase""",      a_		) != do_lower_case
       or normalizer_state.get("""strip_accents""",      a_		) != strip_accents
       or normalizer_state.get("""handle_chinese_chars""",      a_		) != tokenize_chinese_chars
   ):
     _snake_case							:		Dict								=  getattr(a_,      normalizer_state.pop("""type"""		)		)
     _snake_case							:		List[Any]								=  do_lower_case
     _snake_case							:		List[str]								=  strip_accents
     _snake_case							:		Tuple								=  tokenize_chinese_chars
     _snake_case							:		Tuple								=  normalizer_class(**a_		)

   _snake_case							:		List[str]								=  do_lower_case


 def  UpperCamelCase_   (				self:		Any,      a_:		str,      a_:		Optional[int]=None		):




   '''simple docstring'''



   _snake_case							:		Optional[Any]								=  [self.cls_token_id] + token_ids_a + [self.sep_token_id]

   if token_ids_a:
     output += token_ids_a + [self.sep_token_id]

   return output


 def  UpperCamelCase_   (				self:		List[str],      a_:		List[int],      a_:		Optional[List[int]] = None		):




   '''simple docstring'''



   _snake_case							:		Union[str, Any]								=  [self.sep_token_id]
   _snake_case							:		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  UpperCamelCase_   (				self:		Dict,      a_:		str,      a_:		Optional[str] = None		):




   '''simple docstring'''



   _snake_case							:		Union[str, Any]								=  self._tokenizer.model.save(a_,      name=a_		)
   return tuple(a_		)


