






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:
		_a      	=  None


_a      	=  logging.get_logger(__name__)

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

_a      	=  {
    '''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''',
    },
}

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

_a      	=  '''▁'''





class __lowerCamelCase (      __A):





	"""simple docstring"""






	UpperCamelCase__								=      VOCAB_FILES_NAMES
	UpperCamelCase__								=      PRETRAINED_VOCAB_FILES_MAP
	UpperCamelCase__								=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	UpperCamelCase__								=      ["input_ids", "attention_mask"]
	UpperCamelCase__								=      CamembertTokenizer

	def __init__(							self       ,    UpperCAmelCase=None       ,    UpperCAmelCase=None       ,    UpperCAmelCase="<s>"       ,    UpperCAmelCase="</s>"       ,    UpperCAmelCase="</s>"       ,    UpperCAmelCase="<s>"       ,    UpperCAmelCase="<unk>"       ,    UpperCAmelCase="<pad>"       ,    UpperCAmelCase="<mask>"       ,    UpperCAmelCase=["<s>NOTUSED", "</s>NOTUSED"]       ,    **UpperCAmelCase       ,    ):
							"""simple docstring"""







							_UpperCAmelCase									=			AddedToken(_UpperCamelCase       ,    lstrip=_UpperCamelCase       ,    rstrip=_UpperCamelCase    ) if isinstance(_UpperCamelCase       ,    _UpperCamelCase    ) else mask_token

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

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

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = None    ):
							"""simple docstring"""







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

	def        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = None    ):
							"""simple docstring"""







							_UpperCAmelCase									=			[self.sep_token_id]
							_UpperCAmelCase									=			[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        UpperCamelCase    (							self       ,    UpperCAmelCase       ,    UpperCAmelCase = 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(_UpperCamelCase    ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""    )
													return
							_UpperCAmelCase									=			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    ):
													copyfile(self.vocab_file       ,    _UpperCamelCase    )

							return (out_vocab_file,)



from __future__ import annotations

from collections.abc import Generator


def   __SCREAMING_SNAKE_CASE					():
						snake_case_   =	{}
						snake_case_   =	2
						while True:
												snake_case_   =	factor_map.pop(SCREAMING_SNAKE_CASE__  ,		SCREAMING_SNAKE_CASE__       )
												if factor:
																		snake_case_   =	factor + prime
																		while x in factor_map:
																								x += factor
																		snake_case_   =	factor
												else:
																		snake_case_   =	prime
																		yield prime
												prime += 1


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__ = 1E10       ):
						snake_case_   =	sieve()

						snake_case_   =	1
						while True:
												snake_case_   =	next(SCREAMING_SNAKE_CASE__       )
												if (2 * prime * n) > limit:
																		return n
												# Ignore the next prime as the reminder will be 2.
												next(SCREAMING_SNAKE_CASE__       )
												n += 2


if __name__ == "__main__":
					print(solution())