




def  snake_case_					(		SCREAMING_SNAKE_CASE_ = 10_00    )      ->			int:
							lowercase__  :	Union[str, Any]        =							0
							lowercase__  :	List[str]        =							(n - 1) // 3
							total += ((terms) * (6 + (terms - 1) * 3)) // 2  # total of an A.P.
							lowercase__  :	Optional[Any]        =							(n - 1) // 5
							total += ((terms) * (10 + (terms - 1) * 5)) // 2
							lowercase__  :	Dict        =							(n - 1) // 15
							total -= ((terms) * (30 + (terms - 1) * 15)) // 2
							return total


if __name__ == "__main__":
		print(f'{solution() = }')





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

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
						from .tokenization_deberta_va import DebertaVaTokenizer
else:
						__a  :		Optional[Any]		     =   None

__a  :		List[str]		     =   logging.get_logger(__name__)

__a  :		Dict		     =   {'''vocab_file''': '''spm.model''', '''tokenizer_file''': '''tokenizer.json'''}

__a  :		int		     =   {
    '''vocab_file''': {
        '''microsoft/deberta-v2-xlarge''': '''https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xxlarge''': '''https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'''
        ),
        '''microsoft/deberta-v2-xxlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'''
        ),
    }
}

__a  :		Any		     =   {
    '''microsoft/deberta-v2-xlarge''': 5_1_2,
    '''microsoft/deberta-v2-xxlarge''': 5_1_2,
    '''microsoft/deberta-v2-xlarge-mnli''': 5_1_2,
    '''microsoft/deberta-v2-xxlarge-mnli''': 5_1_2,
}

__a  :		Union[str, Any]		     =   {
    '''microsoft/deberta-v2-xlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xlarge-mnli''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge-mnli''': {'''do_lower_case''': False},
}







class 				UpperCAmelCase(					snake_case_					):



	"""simple docstring"""






	a     : List[Any]	  =					VOCAB_FILES_NAMES
	a     : Optional[int]	  =					PRETRAINED_VOCAB_FILES_MAP
	a     : int	  =					PRETRAINED_INIT_CONFIGURATION
	a     : List[str]	  =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	a     : int	  =					DebertaVaTokenizer

	def __init__(					self	,				lowerCamelCase=None	,				lowerCamelCase=None	,				lowerCamelCase=False	,				lowerCamelCase=False	,				lowerCamelCase="[CLS]"	,				lowerCamelCase="[SEP]"	,				lowerCamelCase="[UNK]"	,				lowerCamelCase="[SEP]"	,				lowerCamelCase="[PAD]"	,				lowerCamelCase="[CLS]"	,				lowerCamelCase="[MASK]"	,				**lowerCamelCase	,				) ->      None:





								"""simple docstring"""


								super().__init__(
								    lowerCamelCase	,				tokenizer_file=lowerCamelCase	,				do_lower_case=lowerCamelCase	,				bos_token=lowerCamelCase	,				eos_token=lowerCamelCase	,				unk_token=lowerCamelCase	,				sep_token=lowerCamelCase	,				pad_token=lowerCamelCase	,				cls_token=lowerCamelCase	,				mask_token=lowerCamelCase	,				split_by_punct=lowerCamelCase	,				**lowerCamelCase	,				)

								lowercase__  :	Optional[int]        =							do_lower_case
								lowercase__  :	Optional[Any]        =							split_by_punct
								lowercase__  :	Tuple        =							vocab_file
								lowercase__  :	Optional[int]        =							False if not self.vocab_file else True

	def    __a     (					self	,				lowerCamelCase	,				lowerCamelCase=None    ) ->      List[Any]:





								"""simple docstring"""


								if token_ids_a is None:
															return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								lowercase__  :	Union[str, Any]        =							[self.cls_token_id]
								lowercase__  :	Union[str, Any]        =							[self.sep_token_id]
								return cls + token_ids_a + sep + token_ids_a + sep

	def    __a     (					self	,				lowerCamelCase	,				lowerCamelCase=None	,				lowerCamelCase=False    ) ->      Union[str, Any]:





								"""simple docstring"""


								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 not None:
															return [1] + ([0] * len(lowerCamelCase    )) + [1] + ([0] * len(lowerCamelCase    )) + [1]
								return [1] + ([0] * len(lowerCamelCase    )) + [1]

	def    __a     (					self	,				lowerCamelCase	,				lowerCamelCase=None    ) ->      Optional[int]:





								"""simple docstring"""


								lowercase__  :	Any        =							[self.sep_token_id]
								lowercase__  :	List[str]        =							[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    ) * [0] + len(token_ids_a + sep    ) * [1]







	def    __a     (					self	,				lowerCamelCase	,				lowerCamelCase = None    ) ->      Tuple[str]:





								"""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(lowerCamelCase    ):
															logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""    )
															return
								lowercase__  :	int        =							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    ):
															copyfile(self.vocab_file	,				lowerCamelCase    )

								return (out_vocab_file,)