

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


__lowerCamelCase						    =      logging.get_logger(__name__)

__lowerCamelCase						    =      {
    '''Visual-Attention-Network/van-base''': (
        '''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
    ),
}


class    A__ ( lowerCAmelCase_     ):
    lowercase		   =						'van'



    def __init__(   self						,			UpperCamelCase__=224						,			UpperCamelCase__=3						,			UpperCamelCase__=[7, 3, 3, 3]						,			UpperCamelCase__=[4, 2, 2, 2]						,			UpperCamelCase__=[64, 128, 320, 512]						,			UpperCamelCase__=[3, 3, 12, 3]						,			UpperCamelCase__=[8, 8, 4, 4]						,			UpperCamelCase__="gelu"						,			UpperCamelCase__=0.02						,			UpperCamelCase__=1e-6						,			UpperCamelCase__=1e-2						,			UpperCamelCase__=0.0						,			UpperCamelCase__=0.0						,			**UpperCamelCase__						,			)  -> Optional[Any]:





           '''simple docstring'''
           super().__init__(**__lowerCAmelCase    )
           A_		   = image_size
           A_		   = num_channels
           A_		   = patch_sizes
           A_		   = strides
           A_		   = hidden_sizes
           A_		   = depths
           A_		   = mlp_ratios
           A_		   = hidden_act
           A_		   = initializer_range
           A_		   = layer_norm_eps
           A_		   = layer_scale_init_value
           A_		   = drop_path_rate
           A_		   = dropout_rate



'''simple docstring'''







def  UpperCAmelCase__      ( UpperCAmelCase__ = 1_00			)     ->     int:
       A_		   = n * (n + 1) * (2 * n + 1) / 6
       A_		   = (n * (n + 1) / 2) ** 2
       return int(square_of_sum - sum_of_squares			)


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