
'''simple docstring'''


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


__lowercase							:   Dict					=     logging.get_logger(__name__)

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

class 	__lowercase				(  _lowercase      ,     _lowercase    ):
			lowerCamelCase			:		List[str]	      =			"focalnet"

			def __init__(self			,   A=2_2_4			,   A=4			,   A=3			,   A=9_6			,   A=False			,   A=[1_9_2, 3_8_4, 7_6_8, 7_6_8]			,   A=[2, 2, 6, 2]			,   A=[2, 2, 2, 2]			,   A=[3, 3, 3, 3]			,   A="gelu"			,   A=4.0			,   A=0.0			,   A=0.1			,   A=False			,   A=1E-4			,   A=False			,   A=False			,   A=False			,   A=0.02			,   A=1E-5			,   A=3_2			,   A=None			,   A=None			,   **A			,   ):
								super().__init__(**A      )

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




'''simple docstring'''


def lowercase_	(   _lowercase = 1_000				)     ->							int:
					'''simple docstring'''

					lowerCamelCase_					:      Dict     =		2**power
					lowerCamelCase_					:      Union[str, Any]     =		str(_lowercase				)
					lowerCamelCase_					:      Union[str, Any]     =		list(_lowercase				)
					lowerCamelCase_					:      Dict     =		0

					for i in list_num:
										sum_of_num += int(_lowercase				)

					return sum_of_num


if __name__ == "__main__":
					__lowercase							:   Optional[Any]					=     int(input('''Enter the power of 2: ''').strip())
					print('''2 ^ ''', power, ''' = ''', 2**power)
					__lowercase							:   Tuple					=     solution(power)
					print('''Sum of the digits is: ''', result)


