





"""simple docstring"""
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:
       __UpperCamelCase    :	str						=     None

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

__UpperCamelCase    :	Optional[Any]						=     {'''vocab_file''': '''spm.model''', '''tokenizer_file''': '''tokenizer.json'''}

__UpperCamelCase    :	Tuple						=     {
    '''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'''
        ),
    }
}

__UpperCamelCase    :	Dict						=     {
    '''microsoft/deberta-v2-xlarge''': 512,
    '''microsoft/deberta-v2-xxlarge''': 512,
    '''microsoft/deberta-v2-xlarge-mnli''': 512,
    '''microsoft/deberta-v2-xxlarge-mnli''': 512,
}

__UpperCamelCase    :	Tuple						=     {
    '''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 			a       (      a__     ):
 snake_case__								=					VOCAB_FILES_NAMES
 snake_case__								=					PRETRAINED_VOCAB_FILES_MAP
 snake_case__								=					PRETRAINED_INIT_CONFIGURATION
 snake_case__								=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case__								=					DebertaVaTokenizer



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







  """simple docstring"""






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

  lowerCAmelCase													=   do_lower_case
  lowerCAmelCase													=   split_by_punct
  lowerCAmelCase													=   vocab_file
  lowerCAmelCase													=   False if not self.vocab_file else True



 def       UpperCamelCase__     (    self							,					_snake_case							,					_snake_case=None    ):







  """simple docstring"""






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



 def       UpperCamelCase__     (    self							,					_snake_case							,					_snake_case=None							,					_snake_case=False    ):







  """simple docstring"""






  if already_has_special_tokens:
   return super().get_special_tokens_mask(
       token_ids_a=_snake_case							,					token_ids_a=_snake_case							,					already_has_special_tokens=_snake_case    )

  if token_ids_a is not None:
   return [1] + ([0] * len(_snake_case    )) + [1] + ([0] * len(_snake_case    )) + [1]
  return [1] + ([0] * len(_snake_case    )) + [1]



 def       UpperCamelCase__     (    self							,					_snake_case							,					_snake_case=None    ):







  """simple docstring"""






  lowerCAmelCase													=   [self.sep_token_id]
  lowerCAmelCase													=   [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       UpperCamelCase__     (    self							,					_snake_case							,					_snake_case = 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(_snake_case    ):
   logger.error(F'Vocabulary path ({save_directory}) should be a directory'    )
   return
  lowerCAmelCase													=   os.path.join(
      _snake_case							,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )

  if os.path.abspath(self.vocab_file    ) != os.path.abspath(_snake_case    ):
   copyfile(self.vocab_file							,					_snake_case    )

  return (out_vocab_file,)












"""simple docstring"""
import math

def 		_SCREAMING_SNAKE_CASE (_UpperCAmelCase				:						int ):

 if 1 < number < 4:
  # 2 and 3 are primes
  return True
 elif number < 2 or number % 2 == 0 or number % 3 == 0:
  # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
  return False

 # All primes number are in format of 6k +/- 1
 for i in range(5     ,    int(math.sqrt(_UpperCAmelCase ) + 1 )     ,    6 ):
  if number % i == 0 or number % (i + 2) == 0:
   return False
 return True

def 		_SCREAMING_SNAKE_CASE (_UpperCAmelCase				:						int = 200_0000 ):
 return sum(num for num in range(3     ,    _UpperCAmelCase     ,    2 ) if is_prime(_UpperCAmelCase ) ) + 2 if n > 2 else 0


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





