

"""simple docstring"""






import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_deberta import DebertaTokenizer


if TYPE_CHECKING:
      from transformers.pipelines.conversational import Conversation


lowerCamelCase__			:					Any							  =					logging.get_logger(__name__)

lowerCamelCase__			:					Dict							  =					{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCamelCase__			:					List[Any]							  =					{
    '''vocab_file''': {
        '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json''',
        '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json''',
        '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json''',
        '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json''',
        '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json''',
        '''microsoft/deberta-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt''',
        '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt''',
        '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt''',
        '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt''',
        '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt''',
        '''microsoft/deberta-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'''
        ),
    },
}

lowerCamelCase__			:					Dict							  =					{
    '''microsoft/deberta-base''': 5_12,
    '''microsoft/deberta-large''': 5_12,
    '''microsoft/deberta-xlarge''': 5_12,
    '''microsoft/deberta-base-mnli''': 5_12,
    '''microsoft/deberta-large-mnli''': 5_12,
    '''microsoft/deberta-xlarge-mnli''': 5_12,
}

lowerCamelCase__			:					Optional[Any]							  =					{
    '''microsoft/deberta-base''': {'''do_lower_case''': False},
    '''microsoft/deberta-large''': {'''do_lower_case''': False},
}






class       _UpperCAmelCase     (						__a):
   __a	:    str			   =							VOCAB_FILES_NAMES
   __a	:    Any			   =							PRETRAINED_VOCAB_FILES_MAP
   __a	:    List[str]			   =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __a	:    Any			   =							["""input_ids""", """attention_mask""", """token_type_ids"""]
   __a	:    Optional[Any]			   =							DebertaTokenizer
   def __init__(						self ,						_A=None ,						_A=None ,						_A=None ,						_A="replace" ,						_A="[CLS]" ,						_A="[SEP]" ,						_A="[SEP]" ,						_A="[CLS]" ,						_A="[UNK]" ,						_A="[PAD]" ,						_A="[MASK]" ,						_A=False ,						**_A ,						)      ->      int:






    '''simple docstring'''







    super().__init__(
        _A ,						_A ,						tokenizer_file=_A ,						errors=_A ,						bos_token=_A ,						eos_token=_A ,						unk_token=_A ,						sep_token=_A ,						cls_token=_A ,						pad_token=_A ,						mask_token=_A ,						add_prefix_space=_A ,						**_A ,						)
    _UpperCAmelCase      :							str       =   kwargs.pop("""add_bos_token""" ,						_A       )

    _UpperCAmelCase      :							Dict       =   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
    if pre_tok_state.get("""add_prefix_space""" ,						_A       ) != add_prefix_space:
     _UpperCAmelCase      :							int       =   getattr(_A ,						pre_tok_state.pop("""type"""       )       )
     _UpperCAmelCase      :							List[str]       =   add_prefix_space
     _UpperCAmelCase      :							Dict       =   pre_tok_class(**_A       )

    _UpperCAmelCase      :							List[str]       =   add_prefix_space
   @property
   def 							__snake_case	(						self       )      ->      str:






    '''simple docstring'''







    if self._mask_token is None:
     if self.verbose:
      logger.error("""Using mask_token, but it is not set yet."""       )
     return None
    return str(self._mask_token       )
   @mask_token.setter
   def 							__snake_case	(						self ,						_A       )      ->      Any:






    '''simple docstring'''







    _UpperCAmelCase      :							Union[str, Any]       =   AddedToken(_A ,						lstrip=_A ,						rstrip=_A       ) if isinstance(_A ,						_A       ) else value
    _UpperCAmelCase      :							List[str]       =   value
   def 							__snake_case	(						self ,						_A ,						_A = None       )      ->      List[int]:






    '''simple docstring'''







    if token_ids_a is None:
     return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
    _UpperCAmelCase      :							List[Any]       =   [self.cls_token_id]
    _UpperCAmelCase      :							int       =   [self.sep_token_id]
    return cls + token_ids_a + sep + token_ids_a + sep
   def 							__snake_case	(						self ,						_A ,						_A = None       )      ->      List[int]:






    '''simple docstring'''







    _UpperCAmelCase      :							int       =   [self.sep_token_id]
    _UpperCAmelCase      :							Any       =   [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 							__snake_case	(						self ,						*_A ,						**_A       )      ->      BatchEncoding:






    '''simple docstring'''







    _UpperCAmelCase      :							Union[str, Any]       =   kwargs.get("""is_split_into_words""" ,						_A       )
    assert self.add_prefix_space or not is_split_into_words, (
        f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
        "to use it with pretokenized inputs."
    )

    return super()._batch_encode_plus(*_A ,						**_A       )
   def 							__snake_case	(						self ,						*_A ,						**_A       )      ->      BatchEncoding:






    '''simple docstring'''







    _UpperCAmelCase      :							int       =   kwargs.get("""is_split_into_words""" ,						_A       )

    assert self.add_prefix_space or not is_split_into_words, (
        f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
        "to use it with pretokenized inputs."
    )

    return super()._encode_plus(*_A ,						**_A       )
   def 							__snake_case	(						self ,						_A ,						_A = None       )      ->      Tuple[str]:






    '''simple docstring'''







    _UpperCAmelCase      :							Any       =   self._tokenizer.model.save(_A ,						name=_A       )
    return tuple(_A       )
   def 							__snake_case	(						self ,						_A       )      ->      List[int]:






    '''simple docstring'''







    _UpperCAmelCase      :							int       =   []
    for is_user, text in conversation.iter_texts():
     input_ids.extend(self.encode(_A ,						add_special_tokens=_A       ) + [self.eos_token_id]       )

    if len(_A       ) > self.model_max_length:
     _UpperCAmelCase      :							Union[str, Any]       =   input_ids[-self.model_max_length :]
    return input_ids








"""simple docstring"""






import math
def  UpperCamelCase   (     _lowerCAmelCase       :  int	)			->     bool:

	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(_lowerCAmelCase	) + 1	),					6	):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True
def  UpperCamelCase   (     _lowerCAmelCase       :  int = 2000000	)			->     int:
	return sum(num for num in range(3,					_lowerCAmelCase,					2	) if is_prime(_lowerCAmelCase	)	) + 2 if n > 2 else 0


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





