


"""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


UpperCAmelCase				=						logging.get_logger(__name__)

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

UpperCAmelCase				=						{
    """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"""
        ),
    },
}

UpperCAmelCase				=						{
    """moussaKam/mbarthez""": 1024,
    """moussaKam/barthez""": 1024,
    """moussaKam/barthez-orangesum-title""": 1024,
}

UpperCAmelCase				=						"""▁"""




class 	lowercase__				(					A_				):
   __UpperCAmelCase							       =					VOCAB_FILES_NAMES
   __UpperCAmelCase							       =					PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase							       =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase							       =					['''input_ids''', '''attention_mask''']





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

      _lowerCamelCase	:					List[Any]   =		{} if sp_model_kwargs is None else sp_model_kwargs

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

      _lowerCamelCase	:					Optional[int]   =		vocab_file
      _lowerCamelCase	:					Tuple   =		spm.SentencePieceProcessor(**self.sp_model_kwargs)
      self.sp_model.Load(str(SCREAMING_SNAKE_CASE))

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

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





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = None)  ->  List[int]:

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





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = None      ,   SCREAMING_SNAKE_CASE = False)  ->  List[int]:
      if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=SCREAMING_SNAKE_CASE      ,   token_ids_a=SCREAMING_SNAKE_CASE      ,   already_has_special_tokens=SCREAMING_SNAKE_CASE)

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





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = None)  ->  List[int]:
      _lowerCamelCase	:					Union[str, Any]   =		[self.sep_token_id]
      _lowerCamelCase	:					Tuple   =		[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)  ->  Union[str, Any]:
      return len(self.sp_model)





   def 		UpperCamelCase_  (							self)  ->  Dict:
      _lowerCamelCase	:					Tuple   =		{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE): i for i in range(self.vocab_size)}
      vocab.update(self.added_tokens_encoder)
      return vocab





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





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  str:
      if token in self.fairseq_tokens_to_ids:
         return self.fairseq_tokens_to_ids[token]
      _lowerCamelCase	:					Optional[Any]   =		self.sp_model.PieceToId(SCREAMING_SNAKE_CASE)

      return spm_id if spm_id else self.unk_token_id





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  List[str]:
      if index in self.fairseq_ids_to_tokens:
         return self.fairseq_ids_to_tokens[index]
      return self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE)  ->  str:
      _lowerCamelCase	:					Any   =		[]
      _lowerCamelCase	:					List[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(SCREAMING_SNAKE_CASE) + token
            _lowerCamelCase	:					Any   =		True
            _lowerCamelCase	:					Union[str, Any]   =		[]
         else:
            current_sub_tokens.append(SCREAMING_SNAKE_CASE)
            _lowerCamelCase	:					str   =		False
      out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE)
      return out_string.strip()





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





   def __setstate__(							self      ,   SCREAMING_SNAKE_CASE)  ->  Dict:
      _lowerCamelCase	:					Optional[Any]   =		d

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

      _lowerCamelCase	:					int   =		spm.SentencePieceProcessor(**self.sp_model_kwargs)
      self.sp_model.Load(self.vocab_file)





   def 		UpperCamelCase_  (							self      ,   SCREAMING_SNAKE_CASE      ,   SCREAMING_SNAKE_CASE = None)  ->  Tuple[str]:
      if not os.path.isdir(SCREAMING_SNAKE_CASE):
         logger.error(F'Vocabulary path ({save_directory}) should be a directory')
         return
      _lowerCamelCase	:					Tuple   =		os.path.join(
          SCREAMING_SNAKE_CASE      ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])

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

      return (out_vocab_file,)





"""simple docstring"""
import random

def 				_snake_case      (   __snake_case							:      List[Any]						, __snake_case							:      List[Any]						, __snake_case							:      int   ):




   """simple docstring"""







   _lowerCamelCase	:					List[str]   =		a[left_index]
   _lowerCamelCase	:					Dict   =		left_index + 1
   for j in range(left_index + 1						, __snake_case   ):
      if a[j] < pivot:
         _lowerCamelCase   ,    _lowerCamelCase	:					List[str]   =		a[i], a[j]
         i += 1
   _lowerCamelCase   ,    _lowerCamelCase	:					Optional[int]   =		a[i - 1], a[left_index]
   return i - 1

def 				_snake_case      (   __snake_case							:      Tuple						, __snake_case							:      List[str]						, __snake_case							:      List[str]   ):




   """simple docstring"""







   if left < right:
      _lowerCamelCase	:					Any   =		random.randint(__snake_case						, right - 1   )
      _lowerCamelCase   ,    _lowerCamelCase	:					Optional[Any]   =		(
          a[left],
          a[pivot],
      )  # switches the pivot with the left most bound
      _lowerCamelCase	:					List[str]   =		partition(__snake_case						, __snake_case						, __snake_case   )
      quick_sort_random(
          __snake_case						, __snake_case						, __snake_case   )  # recursive quicksort to the left of the pivot point
      quick_sort_random(
          __snake_case						, pivot_index + 1						, __snake_case   )  # recursive quicksort to the right of the pivot point

def 				_snake_case      (   ):




   """simple docstring"""







   _lowerCamelCase	:					Union[str, Any]   =		input("""Enter numbers separated by a comma:\n"""   ).strip()
   _lowerCamelCase	:					int   =		[int(__snake_case   ) for item in user_input.split(""","""   )]

   quick_sort_random(__snake_case						, 0						, len(__snake_case   )   )

   print(__snake_case   )


if __name__ == "__main__":
 main()

