


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

__A   :    List[Any]											= {"vocab_file": "sentencepiece.bpe.model"}

__A   :    Optional[Any]											= {
    "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   :    Optional[int]											= {
    "moussaKam/mbarthez": 1024,
    "moussaKam/barthez": 1024,
    "moussaKam/barthez-orangesum-title": 1024,
}

__A   :    List[str]											= "▁"






class   __snake_case			(  _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase  					=   VOCAB_FILES_NAMES
    lowercase  					=   PRETRAINED_VOCAB_FILES_MAP
    lowercase  					=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase  					=   ['input_ids', 'attention_mask']

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

      lowerCAmelCase_     : Tuple     =  {} if sp_model_kwargs is None else sp_model_kwargs

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

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

      lowerCAmelCase_     : Union[str, Any]     =  {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

      lowerCAmelCase_     : List[Any]     =  len(self.sp_model						) - 1
      lowerCAmelCase_     : Any     =  {v: k for k, v in self.fairseq_tokens_to_ids.items()}

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

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

    def __lowercase  (  self       :    Union[str, Any]       ,		lowerCamelCase       :    List[int]       ,		lowerCamelCase       :    Optional[List[int]] = None       ,		lowerCamelCase       :    bool = False						)  ->    List[int]:
      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 None:
        return [1] + ([0] * len(lowerCamelCase						)) + [1]
      return [1] + ([0] * len(lowerCamelCase						)) + [1, 1] + ([0] * len(lowerCamelCase						)) + [1]

    def __lowercase  (  self       :    Optional[int]       ,		lowerCamelCase       :    List[int]       ,		lowerCamelCase       :    Optional[List[int]] = None						)  ->    List[int]:
      lowerCAmelCase_     : Dict     =  [self.sep_token_id]
      lowerCAmelCase_     : Optional[Any]     =  [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 __lowercase  (  self       :    Optional[int]						)  ->    Dict:
      return len(self.sp_model						)

    def __lowercase  (  self       :    List[str]						)  ->    int:
      lowerCAmelCase_     : 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 __lowercase  (  self       :    Optional[int]       ,		lowerCamelCase       :    str						)  ->    List[str]:
      return self.sp_model.encode(lowerCamelCase       ,		out_type=lowerCamelCase						)

    def __lowercase  (  self       :    Optional[int]       ,		lowerCamelCase       :    Any						)  ->    Union[str, Any]:
      if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
      lowerCAmelCase_     : str     =  self.sp_model.PieceToId(lowerCamelCase						)

      return spm_id if spm_id else self.unk_token_id

    def __lowercase  (  self       :    str       ,		lowerCamelCase       :    int						)  ->    str:
      if index in self.fairseq_ids_to_tokens:
        return self.fairseq_ids_to_tokens[index]
      return self.sp_model.IdToPiece(lowerCamelCase						)

    def __lowercase  (  self       :    Any       ,		lowerCamelCase       :    Any						)  ->    Dict:
      lowerCAmelCase_     : Optional[int]     =  []
      lowerCAmelCase_     : str     =  """"""
      lowerCAmelCase_     : Optional[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
          lowerCAmelCase_     : Optional[Any]     =  True
          lowerCAmelCase_     : Any     =  []
        else:
          current_sub_tokens.append(lowerCamelCase						)
          lowerCAmelCase_     : List[Any]     =  False
      out_string += self.sp_model.decode(lowerCamelCase						)
      return out_string.strip()

    def __getstate__(  self       :    List[str]						)  ->    Optional[Any]:
      lowerCAmelCase_     : Union[str, Any]     =  self.__dict__.copy()
      lowerCAmelCase_     : Optional[int]     =  None
      return state

    def __setstate__(  self       :    Dict       ,		lowerCamelCase       :    int						)  ->    Optional[Any]:
      lowerCAmelCase_     : Optional[Any]     =  d

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

      lowerCAmelCase_     : str     =  spm.SentencePieceProcessor(**self.sp_model_kwargs						)
      self.sp_model.Load(self.vocab_file						)





    def __lowercase  (  self       :    List[Any]       ,		lowerCamelCase       :    str       ,		lowerCamelCase       :    Optional[str] = None						)  ->    Tuple[str]:
      if not os.path.isdir(lowerCamelCase						):
        logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
        return
      lowerCAmelCase_     : List[str]     =  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:
          lowerCAmelCase_     : Optional[Any]     =  self.sp_model.serialized_model_proto()
          fi.write(lowerCamelCase						)

      return (out_vocab_file,)







'''simple docstring'''






from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__A   :    Tuple											= 10







def 							UpperCamelCase_     (       A__   :  int				,       A__   :  int				,       A__   :  list[int]				,       A__   :  int   ):
  '''simple docstring'''





  for i in range(A__				,       A__   ):
    if array[i] == target:
      return i
  return -1







def 							UpperCamelCase_     (       A__   :  list[int]				,       A__   :  int   ):
  '''simple docstring'''





  lowerCAmelCase_     : Optional[int]     =  0
  lowerCAmelCase_     : Union[str, Any]     =  len(A__   )
  while left <= right:
    if right - left < precision:
      return lin_search(A__				,       A__				,       A__				,       A__   )

    lowerCAmelCase_     : Dict     =  (left + right) // 3 + 1
    lowerCAmelCase_     : List[Any]     =  2 * (left + right) // 3 + 1

    if array[one_third] == target:
      return one_third
    elif array[two_third] == target:
      return two_third

    elif target < array[one_third]:
      lowerCAmelCase_     : List[str]     =  one_third - 1
    elif array[two_third] < target:
      lowerCAmelCase_     : Tuple     =  two_third + 1

    else:
      lowerCAmelCase_     : Tuple     =  one_third + 1
      lowerCAmelCase_     : Any     =  two_third - 1
  else:
    return -1







def 							UpperCamelCase_     (       A__   :  int				,       A__   :  int				,       A__   :  list[int]				,       A__   :  int   ):
  '''simple docstring'''





  if left < right:
    if right - left < precision:
      return lin_search(A__				,       A__				,       A__				,       A__   )
    lowerCAmelCase_     : Dict     =  (left + right) // 3 + 1
    lowerCAmelCase_     : Dict     =  2 * (left + right) // 3 + 1

    if array[one_third] == target:
      return one_third
    elif array[two_third] == target:
      return two_third

    elif target < array[one_third]:
      return rec_ternary_search(A__				,       one_third - 1				,       A__				,       A__   )
    elif array[two_third] < target:
      return rec_ternary_search(two_third + 1				,       A__				,       A__				,       A__   )
    else:
      return rec_ternary_search(one_third + 1				,       two_third - 1				,       A__				,       A__   )
  else:
    return -1


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  __A   :    List[Any]											= input("Enter numbers separated by comma:\n").strip()
  __A   :    Union[str, Any]											= [int(item.strip()) for item in user_input.split(",")]
  assert collection == sorted(collection), F"List must be ordered.\n{collection}."
  __A   :    List[Any]											= int(input("Enter the number to be found in the list:\n").strip())
  __A   :    str											= ite_ternary_search(collection, target)
  __A   :    Dict											= rec_ternary_search(0, len(collection) - 1, collection, target)
  if resulta != -1:
    print(F'''Iterative search: {target} found at positions: {resulta}''')
    print(F'''Recursive search: {target} found at positions: {resulta}''')
  else:
    print("Not found")



