





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



class 					__lowerCAmelCase       (			_a,     _a     ):
			lowerCamelCase_     :     int       			=      '''convnextv2'''






			def __init__(self					,							__magic_name__=3					,							__magic_name__=4					,							__magic_name__=4					,							__magic_name__=None					,							__magic_name__=None					,							__magic_name__="gelu"					,							__magic_name__=0.02					,							__magic_name__=1e-12					,							__magic_name__=0.0					,							__magic_name__=224					,							__magic_name__=None					,							__magic_name__=None					,							**__magic_name__					,							)     ->   Any:


							'''simple docstring'''



							super().__init__(**__magic_name__    )

							snake_case_						:    List[str]				=  num_channels
							snake_case_						:    Optional[Any]				=  patch_size
							snake_case_						:    Tuple				=  num_stages
							snake_case_						:    Optional[int]				=  [96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
							snake_case_						:    List[Any]				=  [3, 3, 9, 3] if depths is None else depths
							snake_case_						:    Optional[Any]				=  hidden_act
							snake_case_						:    Optional[int]				=  initializer_range
							snake_case_						:    Tuple				=  layer_norm_eps
							snake_case_						:    Any				=  drop_path_rate
							snake_case_						:    Optional[int]				=  image_size
							snake_case_						:    Union[str, Any]				=  ['''stem'''] + [F'''stage{idx}''' for idx in range(1					,							len(self.depths    ) + 1    )]
							snake_case_			,							snake_case_						:    List[str]				=  get_aligned_output_features_output_indices(
							    out_features=__magic_name__					,							out_indices=__magic_name__					,							stage_names=self.stage_names    )







from __future__ import annotations






def      lowerCamelCase_						(				_UpperCamelCase ,				_UpperCamelCase ,				_UpperCamelCase )		->						tuple[float, list[float]]:






				"""simple docstring"""


				snake_case_						:    Dict				=  list(range(len(_UpperCamelCase ) ) )
				snake_case_						:    Dict				=  [v / w for v, w in zip(_UpperCamelCase ,				_UpperCamelCase )]
				index.sort(key=lambda _UpperCamelCase : ratio[i] ,				reverse=_UpperCamelCase )

				snake_case_						:    float				=  0
				snake_case_						:    list[float]				=  [0] * len(_UpperCamelCase )
				for i in index:
								if weight[i] <= capacity:
												snake_case_						:    Dict				=  1
												max_value += value[i]
												capacity -= weight[i]
								else:
												snake_case_						:    Union[str, Any]				=  capacity / weight[i]
												max_value += value[i] * capacity / weight[i]
												break

				return max_value, fractions


if __name__ == "__main__":
	import doctest

	doctest.testmod()
