



from math import factorial

A__  :  str								=					{str(d): factorial(d) for d in range(10)}


def 			UpperCamelCase(  __UpperCamelCase							:		int ):
		return sum(DIGIT_FACTORIAL[d] for d in str(__UpperCamelCase ) )


def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     str									= 7 * factorial(9 ) + 1
		return sum(i for i in range(3     ,__UpperCamelCase ) if sum_of_digit_factorial(__UpperCamelCase ) == i )


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












'''simple docstring'''




import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing


class  SCREAMING_SNAKE_CASE    (a__							):


     def __init__(						self						,	_UpperCAmelCase = "▁"						,	_UpperCAmelCase = True						,	_UpperCAmelCase = "<unk>"						,	_UpperCAmelCase = "</s>"						,	_UpperCAmelCase = "<pad>"						,	):

          '''simple docstring'''






          __A						: Dict      =       {
              'pad': {'id': 0, 'token': pad_token},
              'eos': {'id': 1, 'token': eos_token},
              'unk': {'id': 2, 'token': unk_token},
          }

          __A						: List[Any]      =       [None] * len(self.special_tokens)
          for token_dict in self.special_tokens.values():
               __A						: List[str]      =       token_dict['token']

          __A						: str      =       Tokenizer(Unigram())

          __A						: Dict      =       normalizers.Sequence(
              [
                  normalizers.Nmt(),
                  normalizers.NFKC(),
                  normalizers.Replace(Regex(' {2,}')						,	' '),
                  normalizers.Lowercase(),
              ])
          __A						: Union[str, Any]      =       pre_tokenizers.Sequence(
              [
                  pre_tokenizers.Metaspace(replacement=_UpperCAmelCase						,	add_prefix_space=_UpperCAmelCase),
                  pre_tokenizers.Digits(individual_digits=_UpperCAmelCase),
                  pre_tokenizers.Punctuation(),
              ])
          __A						: Any      =       decoders.Metaspace(replacement=_UpperCAmelCase						,	add_prefix_space=_UpperCAmelCase)

          __A						: Dict      =       TemplateProcessing(
              single=F'$A {self.special_tokens["eos"]["token"]}'						,	special_tokens=[(self.special_tokens['eos']['token'], self.special_tokens['eos']['id'])]						,	)

          __A						: Any      =       {
              'model': 'SentencePieceUnigram',
              'replacement': replacement,
              'add_prefix_space': add_prefix_space,
          }

          super().__init__(_UpperCAmelCase						,	_UpperCAmelCase)


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase = 8000						,	_UpperCAmelCase = True						,	):

          '''simple docstring'''






          __A						: str      =       trainers.UnigramTrainer(
              vocab_size=_UpperCAmelCase						,	special_tokens=self.special_tokens_list						,	show_progress=_UpperCAmelCase						,	)

          if isinstance(_UpperCAmelCase						,	_UpperCAmelCase):
               __A						: Union[str, Any]      =       [files]
          self._tokenizer.train(_UpperCAmelCase						,	trainer=_UpperCAmelCase)

          self.add_unk_id()


     def 							SCREAMING_SNAKE_CASE  (						self						,	_UpperCAmelCase						,	_UpperCAmelCase = 8000						,	_UpperCAmelCase = True						,	):

          '''simple docstring'''






          __A						: Dict      =       trainers.UnigramTrainer(
              vocab_size=_UpperCAmelCase						,	special_tokens=self.special_tokens_list						,	show_progress=_UpperCAmelCase						,	)

          self._tokenizer.train_from_iterator(_UpperCAmelCase						,	trainer=_UpperCAmelCase)

          self.add_unk_id()


     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          __A						: Any      =       json.loads(self._tokenizer.to_str())

          __A						: Union[str, Any]      =       self.special_tokens['unk']['id']

          __A						: str      =       Tokenizer.from_str(json.dumps(_UpperCAmelCase))