
"""simple docstring"""




_A     :			str  						=			{}


def     __magic_name__      ( __snake_case							:			int	,					__snake_case							:			int	,					__snake_case							:			int    )					->							int:





       if late == 3 or absent == 2:
              return 0

       # if we have no days left, and have not failed any other rules,
       # we have a prize string
       if days == 0:
              return 1

       # No easy solution, so now we need to do the recursive calculation

       # First, check if the combination is already in the cache, and
       # if yes, return the stored value from there since we already
       # know the number of possible prize strings from this point on
       lowercase       :							str									=				(days, absent, late)
       if key in cache:
              return cache[key]

       # now we calculate the three possible ways that can unfold from
       # this point on, depending on our attendance today

       # 1) if we are late (but not absent), the "absent" counter stays as
       # it is, but the "late" counter increases by one
       lowercase       :							List[Any]									=				_calculate(days - 1	,					SCREAMING_SNAKE_CASE__	,					late + 1    )

       # 2) if we are absent, the "absent" counter increases by 1, and the
       # "late" counter resets to 0
       lowercase       :							Dict									=				_calculate(days - 1	,					absent + 1	,					0    )

       # 3) if we are on time, this resets the "late" counter and keeps the
       # absent counter
       lowercase       :							Optional[Any]									=				_calculate(days - 1	,					SCREAMING_SNAKE_CASE__	,					0    )

       lowercase       :							int									=				state_late + state_absent + state_ontime

       lowercase       :							int									=				prizestrings
       return prizestrings


def     __magic_name__      ( __snake_case							:			int = 30    )					->							Dict:
       return _calculate(SCREAMING_SNAKE_CASE__	,					absent=0	,					late=0    )


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






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


lowerCamelCase		   =			logging.get_logger(__name__)

lowerCamelCase		   =			{
    'microsoft/focalnet-tiny': 'https://huggingface.co/microsoft/focalnet-tiny/resolve/main/config.json',
}




class A    (  UpperCamelCase_       ,				UpperCamelCase_	):
      UpperCamelCase__				:    str ='focalnet'






      def __init__(   self		:	Optional[int]     ,  lowercase_		:	List[Any]=224     ,  lowercase_		:	str=4     ,  lowercase_		:	Any=3     ,  lowercase_		:	Dict=96     ,  lowercase_		:	List[str]=False     ,  lowercase_		:	Any=[192, 384, 768, 768]     ,  lowercase_		:	Dict=[2, 2, 6, 2]     ,  lowercase_		:	Optional[int]=[2, 2, 2, 2]     ,  lowercase_		:	List[Any]=[3, 3, 3, 3]     ,  lowercase_		:	Any="gelu"     ,  lowercase_		:	str=4.0     ,  lowercase_		:	List[Any]=0.0     ,  lowercase_		:	Tuple=0.1     ,  lowercase_		:	Optional[Any]=False     ,  lowercase_		:	Optional[int]=1E-4     ,  lowercase_		:	Dict=False     ,  lowercase_		:	Optional[Any]=False     ,  lowercase_		:	Dict=False     ,  lowercase_		:	List[Any]=0.02     ,  lowercase_		:	Any=1E-5     ,  lowercase_		:	Any=32     ,  lowercase_		:	List[str]=None     ,  lowercase_		:	int=None     ,  **lowercase_		:	Optional[Any]     ,  )   ->		Optional[Any]:
             """simple docstring"""




             super().__init__(**lowercase_					)

             _lowerCamelCase			:						Union[str, Any]            =image_size
             _lowerCamelCase			:						str            =patch_size
             _lowerCamelCase			:						str            =num_channels
             _lowerCamelCase			:						Tuple            =embed_dim
             _lowerCamelCase			:						Dict            =use_conv_embed
             _lowerCamelCase			:						int            =hidden_sizes
             _lowerCamelCase			:						str            =depths
             _lowerCamelCase			:						int            =focal_levels
             _lowerCamelCase			:						List[Any]            =focal_windows
             _lowerCamelCase			:						List[Any]            =hidden_act
             _lowerCamelCase			:						int            =mlp_ratio
             _lowerCamelCase			:						Any            =hidden_dropout_prob
             _lowerCamelCase			:						Optional[Any]            =drop_path_rate
             _lowerCamelCase			:						int            =use_layerscale
             _lowerCamelCase			:						str            =layerscale_value
             _lowerCamelCase			:						Dict            =use_post_layernorm
             _lowerCamelCase			:						str            =use_post_layernorm_in_modulation
             _lowerCamelCase			:						List[Any]            =normalize_modulator
             _lowerCamelCase			:						Optional[Any]            =initializer_range
             _lowerCamelCase			:						List[str]            =layer_norm_eps
             _lowerCamelCase			:						Optional[int]            =encoder_stride
             _lowerCamelCase			:						List[str]            =['stem'] + [F'''stage{idx}''' for idx in range(1     ,  len(self.depths					) + 1					)]
             _lowerCamelCase      ,	_lowerCamelCase			:						Union[str, Any]            =get_aligned_output_features_output_indices(
                 out_features=lowercase_     ,  out_indices=lowercase_     ,  stage_names=self.stage_names					)


