





"""simple docstring"""




from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


_lowerCAmelCase    : Tuple							=							logging.get_logger(__name__)

_lowerCAmelCase    : Any							=							{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

_lowerCAmelCase    : Optional[Any]							=							{
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

_lowerCAmelCase    : Dict							=							{
    'facebook/blenderbot_small-90M': 5_12,
}






class      UpperCAmelCase_  (    _UpperCamelCase						):
      __SCREAMING_SNAKE_CASE						:       int								=			VOCAB_FILES_NAMES
      __SCREAMING_SNAKE_CASE						:       Any								=			PRETRAINED_VOCAB_FILES_MAP
      __SCREAMING_SNAKE_CASE						:       Dict								=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __SCREAMING_SNAKE_CASE						:       Any								=			BlenderbotSmallTokenizer



      def __init__(					self					:     Optional[Any]					,     A					:     str=None					,     A					:     Union[str, Any]=None					,     A					:     Dict="<|endoftext|>"					,     A					:     Optional[Any]="<|endoftext|>"					,     A					:     List[str]="<|endoftext|>"					,     A					:     Union[str, Any]=False					,     A					:     Any=True					,     **A					:     Any					,     ):
           super().__init__(
               ByteLevelBPETokenizer(
                   vocab=A					,     merges=A					,     add_prefix_space=A					,     trim_offsets=A					,     )					,     bos_token=A					,     eos_token=A					,     unk_token=A					,     **A					,     )
           _UpperCAmelCase      :     Union[str, Any]        =   add_prefix_space



      def 						snake_case_ (					self					:     str					,     A					:     List[str]					,     A					:     List[Any]=None						):
           _UpperCAmelCase      :     Dict        =   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
                return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



      def 						snake_case_ (					self					:     Dict					,     A					:     str					,     A					:     Union[str, Any] = None						):
           _UpperCAmelCase      :     List[Any]        =   [self.sep_token_id]
           _UpperCAmelCase      :     Dict        =   [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]





"""simple docstring"""




def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						Dict=28_123    )  ->       List[str]:





     '''simple docstring'''

     _UpperCAmelCase      :     List[Any]        =   [1] * (limit + 1)

     for i in range(2						,  int(limit**0.5    ) + 1    ):
          sum_divs[i * i] += i
          for k in range(i + 1						,  limit // i + 1    ):
               sum_divs[k * i] += k + i

     _UpperCAmelCase      :     Any        =   set()
     _UpperCAmelCase      :     List[str]        =   0

     for n in range(1						,  limit + 1    ):
          if sum_divs[n] > n:
               abundants.add(SCREAMING_SNAKE_CASE__    )

          if not any((n - a in abundants) for a in abundants    ):
               res += n

     return res


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