

'''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_			(    _snake_case							):






     '''simple docstring'''



     UpperCAmelCase_						:     Optional[Any]  		=  VOCAB_FILES_NAMES
     UpperCAmelCase_						:     Optional[int]  		=  PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase_						:     Dict  		=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase_						:     int  		=  ["""input_ids""", """attention_mask"""]


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

      UpperCAmelCase	:     str						 =			{} if sp_model_kwargs is None else sp_model_kwargs

      super().__init__(
          bos_token=lowercase_					,      eos_token=lowercase_					,      unk_token=lowercase_					,      sep_token=lowercase_					,      cls_token=lowercase_					,      pad_token=lowercase_					,      mask_token=lowercase_					,      additional_special_tokens=lowercase_					,      sp_model_kwargs=self.sp_model_kwargs					,      **lowercase_					,      )
      UpperCAmelCase	:     Tuple						 =			spm.SentencePieceProcessor(**self.sp_model_kwargs	)
      self.sp_model.Load(str(lowercase_	)	)
      UpperCAmelCase	:     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>
      UpperCAmelCase	:     Any						 =			{'<s>NOTUSED': 0, '<pad>': 1, '</s>NOTUSED': 2, '<unk>': 3}
      UpperCAmelCase	:     Union[str, Any]						 =			len(self.fairseq_tokens_to_ids	)
      UpperCAmelCase	:     Optional[Any]						 =			len(self.sp_model	) + len(self.fairseq_tokens_to_ids	)
      UpperCAmelCase	:     Tuple						 =			{v: k for k, v in self.fairseq_tokens_to_ids.items()}


     def        UpperCAmelCase_	(		self			:					Union[str, Any]					,      lowercase_			:					List[int]					,      lowercase_			:					Optional[List[int]] = None	)						->     List[int]:

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


     def        UpperCAmelCase_	(		self			:					Any					,      lowercase_			:					List[int]					,      lowercase_			:					Optional[List[int]] = None					,      lowercase_			:					bool = False	)						->     List[int]:
      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=lowercase_					,      token_ids_a=lowercase_					,      already_has_special_tokens=lowercase_	)

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


     def        UpperCAmelCase_	(		self			:					Union[str, Any]					,      lowercase_			:					List[int]					,      lowercase_			:					Optional[List[int]] = None	)						->     List[int]:
      UpperCAmelCase	:     List[Any]						 =			[self.sep_token_id]
      UpperCAmelCase	:     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			:					Tuple	)						->     Optional[int]:
      return len(self.fairseq_tokens_to_ids	) + len(self.sp_model	)


     def        UpperCAmelCase_	(		self			:					Any	)						->     Tuple:
      UpperCAmelCase	:     Any						 =			{self.convert_ids_to_tokens(lowercase_	): i for i in range(self.vocab_size	)}
      vocab.update(self.added_tokens_encoder	)
      return vocab


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


     def        UpperCAmelCase_	(		self			:					int					,      lowercase_			:					Union[str, Any]	)						->     Optional[int]:
      if token in self.fairseq_tokens_to_ids:
       return self.fairseq_tokens_to_ids[token]
      elif self.sp_model.PieceToId(lowercase_	) == 0:
       # Convert sentence piece unk token to fairseq unk token index
       return self.unk_token_id
      return self.fairseq_offset + self.sp_model.PieceToId(lowercase_	)


     def        UpperCAmelCase_	(		self			:					Any					,      lowercase_			:					Union[str, Any]	)						->     Optional[Any]:
      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        UpperCAmelCase_	(		self			:					Optional[Any]					,      lowercase_			:					str	)						->     List[Any]:
      UpperCAmelCase	:     Optional[Any]						 =			[]
      UpperCAmelCase	:     Union[str, Any]						 =			''
      UpperCAmelCase	:     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(lowercase_	) + token
        UpperCAmelCase	:     Optional[Any]						 =			True
        UpperCAmelCase	:     List[Any]						 =			[]
       else:
        current_sub_tokens.append(lowercase_	)
        UpperCAmelCase	:     List[str]						 =			False
      out_string += self.sp_model.decode(lowercase_	)
      return out_string.strip()


     def __getstate__(		self			:					int	)						->     int:
      UpperCAmelCase	:     List[str]						 =			self.__dict__.copy()
      UpperCAmelCase	:     Dict						 =			None
      return state


     def __setstate__(		self			:					Union[str, Any]					,      lowercase_			:					Optional[Any]	)						->     Tuple:
      UpperCAmelCase	:     List[Any]						 =			d

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

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




     def        UpperCAmelCase_	(		self			:					Optional[int]					,      lowercase_			:					str					,      lowercase_			:					Optional[str] = None	)						->     Tuple[str]:
      if not os.path.isdir(lowercase_	):
       logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
       return
      UpperCAmelCase	:     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:
        UpperCAmelCase	:     Any						 =			self.sp_model.serialized_model_proto()
        fi.write(lowercase_	)

      return (out_vocab_file,)







'''simple docstring'''

from __future__ import annotations




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     ):
 if len(UpperCAmelCase_     ) == 0:
  raise ValueError('find_max() arg is an empty sequence'     )
 if (
     left >= len(UpperCAmelCase_     )
     or left < -len(UpperCAmelCase_     )
     or right >= len(UpperCAmelCase_     )
     or right < -len(UpperCAmelCase_     )
 ):
  raise IndexError('list index out of range'     )
 if left == right:
  return nums[left]
 UpperCAmelCase	:     Optional[int]						 =			(left + right) >> 1  # the middle
 UpperCAmelCase	:     Any						 =			find_max(UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     )  # find max in range[left, mid]
 UpperCAmelCase	:     Union[str, Any]						 =			find_max(UpperCAmelCase_  ,	mid + 1  ,	UpperCAmelCase_     )  # find max in range[mid + 1, right]

 return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)




