






'''simple docstring'''






from itertools import permutations




def        _SCREAMING_SNAKE_CASE  (				A  :       tuple  )    -> bool:







   """simple docstring"""
   if num[3] % 2 != 0:
      return False

   if (num[2] + num[3] + num[4]) % 3 != 0:
      return False

   if num[5] % 5 != 0:
      return False

   __snake_case				:      List[str]     							= [7, 11, 13, 17]
   for i, test in enumerate(A  ):
      if (num[i + 4] * 1_00 + num[i + 5] * 10 + num[i + 6]) % test != 0:
         return False
   return True




def        _SCREAMING_SNAKE_CASE  (				A  :       int = 10  )    -> int:







   """simple docstring"""
   return sum(
       int(''.join(map(A  ,		A  )  )  )
       for num in permutations(range(A  )  )
       if is_substring_divisible(A  )  )


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







'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A    	=   logging.get_logger(__name__)

__A    	=   {
    '''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}




class a_    (    UpperCamelCase_							):
   _snake_case        =							"""vit_msn"""







   def __init__(self					,   __a=7_6_8					,   __a=1_2					,   __a=1_2					,   __a=3_0_7_2					,   __a="gelu"					,   __a=0.0					,   __a=0.0					,   __a=0.02					,   __a=1E-06					,   __a=2_2_4					,   __a=1_6					,   __a=3					,   __a=True					,   **__a					,   )			->      Any:
      """simple docstring"""






      super().__init__(**__a)

      __snake_case				:      List[str]     							= hidden_size
      __snake_case				:      Optional[int]     							= num_hidden_layers
      __snake_case				:      Optional[Any]     							= num_attention_heads
      __snake_case				:      str     							= intermediate_size
      __snake_case				:      List[str]     							= hidden_act
      __snake_case				:      List[Any]     							= hidden_dropout_prob
      __snake_case				:      Tuple     							= attention_probs_dropout_prob
      __snake_case				:      List[str]     							= initializer_range
      __snake_case				:      Optional[int]     							= layer_norm_eps
      __snake_case				:      Dict     							= image_size
      __snake_case				:      int     							= patch_size
      __snake_case				:      Dict     							= num_channels
      __snake_case				:      Tuple     							= qkv_bias