


"""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


__lowercase    					=      logging.get_logger(__name__)

__lowercase    					=      {"""vocab_file""": """sentencepiece.bpe.model"""}

__lowercase    					=      {
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

__lowercase    					=      {
    """camembert-base""": 512,
}

__lowercase    					=      """▁"""






class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase       :							List[str]	=       VOCAB_FILES_NAMES
    UpperCAmelCase       :							List[str]	=       PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase       :							List[str]	=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase       :							Dict	=       ["""input_ids""", """attention_mask"""]






    def __init__(					self				:    Optional[int]				, __UpperCAmelCase				:    Union[str, Any]				, __UpperCAmelCase				:    Tuple="<s>"				, __UpperCAmelCase				:    List[str]="</s>"				, __UpperCAmelCase				:    int="</s>"				, __UpperCAmelCase				:    List[Any]="<s>"				, __UpperCAmelCase				:    Optional[int]="<unk>"				, __UpperCAmelCase				:    Any="<pad>"				, __UpperCAmelCase				:    Optional[Any]="<mask>"				, __UpperCAmelCase				:    Tuple=["<s>NOTUSED", "</s>NOTUSED"]				, __UpperCAmelCase				:    Optional[Dict[str, Any]] = None				, **__UpperCAmelCase				:    List[Any]				, ):
      # Mask token behave like a normal word, i.e. include the space before it
      a						:		Any      							=			AddedToken(__UpperCAmelCase				, lstrip=__UpperCAmelCase				, rstrip=__UpperCAmelCase) if isinstance(__UpperCAmelCase				, __UpperCAmelCase) else mask_token

      a						:		Optional[int]      							=			{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=__UpperCAmelCase				, eos_token=__UpperCAmelCase				, unk_token=__UpperCAmelCase				, sep_token=__UpperCAmelCase				, cls_token=__UpperCAmelCase				, pad_token=__UpperCAmelCase				, mask_token=__UpperCAmelCase				, additional_special_tokens=__UpperCAmelCase				, sp_model_kwargs=self.sp_model_kwargs				, **__UpperCAmelCase				, )
      a						:		str      							=			spm.SentencePieceProcessor(**self.sp_model_kwargs)
      self.sp_model.Load(str(__UpperCAmelCase))
      a						:		List[Any]      							=			vocab_file
      # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
      # sentencepiece vocabulary (this is the case for <s> and </s>
      a						:		Optional[int]      							=			{"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
      a						:		int      							=			len(self.fairseq_tokens_to_ids)
      a						:		Union[str, Any]      							=			len(self.sp_model) + len(self.fairseq_tokens_to_ids)
      a						:		Any      							=			{v: k for k, v in self.fairseq_tokens_to_ids.items()}






    def 	__snake_case							(					self				:    str				, __UpperCAmelCase				:    List[int]				, __UpperCAmelCase				:    Optional[List[int]] = None):

      if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      a						:		int      							=			[self.cls_token_id]
      a						:		int      							=			[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep






    def 	__snake_case							(					self				:    str				, __UpperCAmelCase				:    List[int]				, __UpperCAmelCase				:    Optional[List[int]] = None				, __UpperCAmelCase				:    bool = False):
      if already_has_special_tokens:
        return super().get_special_tokens_mask(
            token_ids_a=__UpperCAmelCase				, token_ids_a=__UpperCAmelCase				, already_has_special_tokens=__UpperCAmelCase)

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






    def 	__snake_case							(					self				:    Optional[Any]				, __UpperCAmelCase				:    List[int]				, __UpperCAmelCase				:    Optional[List[int]] = None):
      a						:		List[str]      							=			[self.sep_token_id]
      a						:		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 	__snake_case							(					self				:    str):
      return len(self.fairseq_tokens_to_ids) + len(self.sp_model)






    def 	__snake_case							(					self				:    Union[str, Any]):
      a						:		Any      							=			{self.convert_ids_to_tokens(__UpperCAmelCase): i for i in range(self.vocab_size)}
      vocab.update(self.added_tokens_encoder)
      return vocab






    def 	__snake_case							(					self				:    str				, __UpperCAmelCase				:    str):
      return self.sp_model.encode(__UpperCAmelCase				, out_type=__UpperCAmelCase)






    def 	__snake_case							(					self				:    List[Any]				, __UpperCAmelCase				:    Dict):
      if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
      elif self.sp_model.PieceToId(__UpperCAmelCase) == 0:
        # Convert sentence piece unk token to fairseq unk token index
        return self.unk_token_id
      return self.fairseq_offset + self.sp_model.PieceToId(__UpperCAmelCase)






    def 	__snake_case							(					self				:    Dict				, __UpperCAmelCase				:    Optional[int]):
      if index in self.fairseq_ids_to_tokens:
        return self.fairseq_ids_to_tokens[index]
      return self.sp_model.IdToPiece(index - self.fairseq_offset)






    def 	__snake_case							(					self				:    Optional[Any]				, __UpperCAmelCase				:    Tuple):
      a						:		int      							=			[]
      a						:		Dict      							=			""
      a						:		List[Any]      							=			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(__UpperCAmelCase) + token
          a						:		str      							=			True
          a						:		str      							=			[]
        else:
          current_sub_tokens.append(__UpperCAmelCase)
          a						:		str      							=			False
      out_string += self.sp_model.decode(__UpperCAmelCase)
      return out_string.strip()






    def __getstate__(					self				:    Tuple):
      a						:		Any      							=			self.__dict__.copy()
      a						:		Optional[Any]      							=			None
      return state






    def __setstate__(					self				:    Optional[int]				, __UpperCAmelCase				:    List[str]):
      a						:		Dict      							=			d

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

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






    def 	__snake_case							(					self				:    int				, __UpperCAmelCase				:    str				, __UpperCAmelCase				:    Optional[str] = None):
      if not os.path.isdir(__UpperCAmelCase):
        logger.error(f'''Vocabulary path ({save_directory}) should be a directory''')
        return
      a						:		Optional[Any]      							=			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:
          a						:		List[Any]      							=			self.sp_model.serialized_model_proto()
          fi.write(__UpperCAmelCase)

      return (out_vocab_file,)










"""simple docstring"""







class 						_A  :







    """simple docstring"""




    def __init__(					self				:    int				, __UpperCAmelCase				:    int):
      a						:		Tuple      							=			size
      a						:		Dict      							=			[0] * size
      a						:		Optional[int]      							=			[0] * size






    @staticmethod
    def 	__snake_case							(					__UpperCAmelCase				:    int):
      return index | (index + 1)






    @staticmethod
    def 	__snake_case							(					__UpperCAmelCase				:    int):
      return (index & (index + 1)) - 1






    def 	__snake_case							(					self				:    List[str]				, __UpperCAmelCase				:    int				, __UpperCAmelCase				:    int):
      a						:		Union[str, Any]      							=			value
      while index < self.size:
        a						:		Dict      							=			self.get_prev(__UpperCAmelCase) + 1
        if current_left_border == index:
          a						:		Optional[int]      							=			value
        else:
          a						:		Any      							=			max(__UpperCAmelCase				, __UpperCAmelCase				, __UpperCAmelCase)
        a						:		Optional[int]      							=			self.get_next(__UpperCAmelCase)






    def 	__snake_case							(					self				:    Union[str, Any]				, __UpperCAmelCase				:    int				, __UpperCAmelCase				:    int):
      right -= 1  # Because of right is exclusive
      a						:		List[str]      							=			0
      while left <= right:
        a						:		Dict      							=			self.get_prev(__UpperCAmelCase)
        if left <= current_left:
          a						:		Optional[int]      							=			max(__UpperCAmelCase				, self.tree[right])
          a						:		Optional[Any]      							=			current_left
        else:
          a						:		List[str]      							=			max(__UpperCAmelCase				, self.arr[right])
          right -= 1
      return result


if __name__ == "__main__":
 import doctest

 doctest.testmod()






