


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


__snake_case   							=						logging.get_logger(__name__)

__snake_case   							=						{
    '''facebook/convnextv2-tiny-1k-224''': '''https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json''',
}



class 	__lowerCamelCase			(_a				,      _a						):
       _lowercase											=     """convnextv2"""







       def __init__(			self: int,A_: List[str]=3,A_: str=4,A_: int=4,A_: List[str]=None,A_: Any=None,A_: List[str]="gelu",A_: Any=0.0_2,A_: int=1E-12,A_: List[Any]=0.0,A_: List[Any]=224,A_: List[Any]=None,A_: List[Any]=None,**A_: int,):






            '''simple docstring'''




            super().__init__(**A_					)

            __UpperCamelCase =			num_channels
            __UpperCamelCase =			patch_size
            __UpperCamelCase =			num_stages
            __UpperCamelCase =			[96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
            __UpperCamelCase =			[3, 3, 9, 3] if depths is None else depths
            __UpperCamelCase =			hidden_act
            __UpperCamelCase =			initializer_range
            __UpperCamelCase =			layer_norm_eps
            __UpperCamelCase =			drop_path_rate
            __UpperCamelCase =			image_size
            __UpperCamelCase =			['stem'] + [F'''stage{idx}''' for idx in range(1,len(self.depths					) + 1					)]
            __UpperCamelCase,    __UpperCamelCase =			get_aligned_output_features_output_indices(
                out_features=A_,out_indices=A_,stage_names=self.stage_names					)






def 		_A		(		_lowercase = 1_00 )					-> int:


     """simple docstring"""


     __UpperCamelCase =			0
     __UpperCamelCase =			0
     for i in range(1					,  n + 1 ):
          sum_of_squares += i**2
          sum_of_ints += i
     return sum_of_ints**2 - sum_of_squares


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


