





from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


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

__lowerCamelCase :  int										=  {
    """google/bit-50""": """https://huggingface.co/google/bit-50/resolve/main/config.json""",
}



class       A__     ( __snake_case ,     __snake_case    ):
      _UpperCAmelCase			:Optional[Any]							=     'bit'
      _UpperCAmelCase			:Union[str, Any]							=     ['preactivation', 'bottleneck']
      _UpperCAmelCase			:Any							=     ['SAME', 'VALID']





      def __init__(				self ,							A_=3 ,							A_=64 ,							A_=[256, 512, 1024, 2048] ,							A_=[3, 4, 6, 3] ,							A_="preactivation" ,							A_="relu" ,							A_=None ,							A_=32 ,							A_=0.0 ,							A_=False ,							A_=32 ,							A_=1 ,							A_=None ,							A_=None ,							**A_ ,							):
       '''simple docstring'''




       super().__init__(**A_     )
       if layer_type not in self.layer_types:
        raise ValueError(F"""layer_type={layer_type} is not one of {",".join(self.layer_types     )}"""     )
       if global_padding is not None:
        if global_padding.upper() in self.supported_padding:
         UpperCamelCase			:      Optional[Any] 			=     global_padding.upper()
        else:
         raise ValueError(F"""Padding strategy {global_padding} not supported"""     )
       UpperCamelCase			:      Dict 			=     num_channels
       UpperCamelCase			:      int 			=     embedding_size
       UpperCamelCase			:      Optional[int] 			=     hidden_sizes
       UpperCamelCase			:      Union[str, Any] 			=     depths
       UpperCamelCase			:      Any 			=     layer_type
       UpperCamelCase			:      Tuple 			=     hidden_act
       UpperCamelCase			:      List[Any] 			=     global_padding
       UpperCamelCase			:      Tuple 			=     num_groups
       UpperCamelCase			:      List[str] 			=     drop_path_rate
       UpperCamelCase			:      Union[str, Any] 			=     embedding_dynamic_padding
       UpperCamelCase			:      Union[str, Any] 			=     output_stride
       UpperCamelCase			:      Union[str, Any] 			=     width_factor

       UpperCamelCase			:      Tuple 			=     ["stem"] + [F"""stage{idx}""" for idx in range(1 ,							len(A_     ) + 1     )]
       UpperCamelCase			,					UpperCamelCase			:      Any 			=     get_aligned_output_features_output_indices(
           out_features=A_ ,							out_indices=A_ ,							stage_names=self.stage_names     )







from __future__ import annotations



def 	A_       (  _lowerCAmelCase  )		->				list[int]:
 UpperCamelCase			:      Optional[Any] 			=     [True] * limit
 UpperCamelCase			:      Optional[Any] 			=     False
 UpperCamelCase			:      List[str] 			=     False
 UpperCamelCase			:      Tuple 			=     True

 for i in range(3							,     int(limit**0.5 + 1  )							,     2  ):
  UpperCamelCase			:      Optional[Any] 			=     i * 2
  while index < limit:
   UpperCamelCase			:      int 			=     False
   UpperCamelCase			:      Optional[int] 			=     index + i

 UpperCamelCase			:      Any 			=     [2]

 for i in range(3							,     _lowerCAmelCase							,     2  ):
  if is_prime[i]:
   primes.append(_lowerCAmelCase  )

 return primes



def 	A_       (  _lowerCAmelCase = 100_0000  )		->				int:
 UpperCamelCase			:      Union[str, Any] 			=     prime_sieve(_lowerCAmelCase  )
 UpperCamelCase			:      List[str] 			=     0
 UpperCamelCase			:      Union[str, Any] 			=     0

 for i in range(len(_lowerCAmelCase  )  ):
  for j in range(i + length							,     len(_lowerCAmelCase  )  ):
   UpperCamelCase			:      Dict 			=     sum(primes[i:j]  )
   if sol >= ceiling:
    break

   if sol in primes:
    UpperCamelCase			:      int 			=     j - i
    UpperCamelCase			:      Dict 			=     sol

 return largest


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