




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
    from .tokenization_camembert import CamembertTokenizer
else:
    snake_case_           =      None


snake_case_           =      logging.get_logger(__name__)

snake_case_           =      {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

snake_case_           =      {
    'vocab_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/tokenizer.json',
    },
}

snake_case_           =      {
    'camembert-base': 512,
}

snake_case_           =      '▁'

class 		SCREAMING_SNAKE_CASE__    (	_UpperCAmelCase  ):
      A_						:    Any							=   VOCAB_FILES_NAMES
      A_						:    Any							=   PRETRAINED_VOCAB_FILES_MAP
      A_						:    int							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      A_						:    Tuple							=   ['input_ids', 'attention_mask']
      A_						:    Dict							=   CamembertTokenizer


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





         """simple docstring"""



         __snake_case								=       AddedToken(_SCREAMING_SNAKE_CASE    ,      lstrip=_SCREAMING_SNAKE_CASE    ,      rstrip=_SCREAMING_SNAKE_CASE				) if isinstance(_SCREAMING_SNAKE_CASE    ,      _SCREAMING_SNAKE_CASE				) else mask_token

         super().__init__(
             _SCREAMING_SNAKE_CASE    ,      tokenizer_file=_SCREAMING_SNAKE_CASE    ,      bos_token=_SCREAMING_SNAKE_CASE    ,      eos_token=_SCREAMING_SNAKE_CASE    ,      sep_token=_SCREAMING_SNAKE_CASE    ,      cls_token=_SCREAMING_SNAKE_CASE    ,      unk_token=_SCREAMING_SNAKE_CASE    ,      pad_token=_SCREAMING_SNAKE_CASE    ,      mask_token=_SCREAMING_SNAKE_CASE    ,      additional_special_tokens=_SCREAMING_SNAKE_CASE    ,      **_SCREAMING_SNAKE_CASE    ,      )

         __snake_case								=       vocab_file
         __snake_case								=       False if not self.vocab_file else True


      def        a			(self	:				str    ,      a__	:				Optional[Any]    ,      a__	:				str = None				):





         """simple docstring"""



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


      def        a			(self	:				Optional[int]    ,      a__	:				int    ,      a__	:				Tuple = None				):





         """simple docstring"""



         __snake_case								=       [self.sep_token_id]
         __snake_case								=       [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]


      def        a			(self	:				List[str]    ,      a__	:				Optional[Any]    ,      a__	:				Optional[Any] = None				):





         """simple docstring"""



         if not self.can_save_slow_tokenizer:
            raise ValueError(
                '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                '''tokenizer.'''				)

         if not os.path.isdir(_SCREAMING_SNAKE_CASE				):
            logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
            return
         __snake_case								=       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				):
            copyfile(self.vocab_file    ,      _SCREAMING_SNAKE_CASE				)

         return (out_vocab_file,)








import math






def lowerCamelCase__   (							snake_case_     :  int	)				->    list[int]:
   __snake_case								=       []
   __snake_case								=       2
   __snake_case								=       int(math.sqrt(snake_case_	)	)  # Size of every segment
   __snake_case								=       [True] * (end + 1)
   __snake_case								=       []

   while start <= end:
      if temp[start] is True:
         in_prime.append(snake_case_	)
         for i in range(start * start	,				end + 1	,				snake_case_	):
            __snake_case								=       False
      start += 1
   prime += in_prime

   __snake_case								=       end + 1
   __snake_case								=       min(2 * end	,				snake_case_	)

   while low <= n:
      __snake_case								=       [True] * (high - low + 1)
      for each in in_prime:
         __snake_case								=       math.floor(low / each	) * each
         if t < low:
            t += each

         for j in range(snake_case_	,				high + 1	,				snake_case_	):
            __snake_case								=       False

      for j in range(len(snake_case_	)	):
         if temp[j] is True:
            prime.append(j + low	)

      __snake_case								=       high + 1
      __snake_case								=       min(high + end	,				snake_case_	)

   return prime







print(sieve(10**6))

