


def  __snake_case       (   UpperCamelCase__ ,			UpperCamelCase__ ,			UpperCamelCase__ ,			UpperCamelCase__ ,			UpperCamelCase__ ,			)      ->		Union[str, Any]:







		"""simple docstring"""





		A					       = [redshift, radiation_density, matter_density, dark_energy]
		if any(p < 0 for p in parameters	):
				raise ValueError('All input parameters must be positive'	)

		if any(p > 1 for p in parameters[1:4]	):
				raise ValueError('Relative densities cannot be greater than one'	)
		else:
				A					       = 1 - (matter_density + radiation_density + dark_energy)

				A					       = (
				    radiation_density * (redshift + 1) ** 4
				    + matter_density * (redshift + 1) ** 3
				    + curvature * (redshift + 1) ** 2
				    + dark_energy
				)

				A					       = hubble_constant * e_a ** (1 / 2)
				return hubble


if __name__ == "__main__":
	import doctest

	# run doctest
	doctest.testmod()

	# demo LCDM approximation
	UpperCamelCase						:				str             =      0.3

	print(
	    hubble_parameter(
	        hubble_constant=68.3,
	        radiation_density=1E-4,
	        matter_density=matter_density,
	        dark_energy=1 - matter_density,
	        redshift=0,
	    )
	)









"""simple docstring"""


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


UpperCamelCase						:				int             =      logging.get_logger(__name__)

UpperCamelCase						:				Optional[int]             =      {
    "google/bit-50": "https://huggingface.co/google/bit-50/resolve/main/config.json",
}



class 			lowerCamelCase__						(   UpperCAmelCase_							,    UpperCAmelCase_			):
						lowerCAmelCase       =     """bit"""
						lowerCAmelCase       =     ["""preactivation""", """bottleneck"""]
						lowerCAmelCase       =     ["""SAME""", """VALID"""]







						def __init__(							self   :    List[str]			,			_lowercase   :    int=3			,			_lowercase   :    List[str]=64			,			_lowercase   :    Optional[int]=[256, 512, 1_024, 2_048]			,			_lowercase   :    Optional[int]=[3, 4, 6, 3]			,			_lowercase   :    int="preactivation"			,			_lowercase   :    Union[str, Any]="relu"			,			_lowercase   :    List[Any]=None			,			_lowercase   :    Tuple=32			,			_lowercase   :    Optional[int]=0.0			,			_lowercase   :    Union[str, Any]=False			,			_lowercase   :    Dict=32			,			_lowercase   :    Union[str, Any]=1			,			_lowercase   :    List[Any]=None			,			_lowercase   :    Any=None			,			**_lowercase   :    str			,			):
								super().__init__(**_lowercase		)
								if layer_type not in self.layer_types:
										raise ValueError(f'layer_type={layer_type} is not one of {",".join(self.layer_types		)}'		)
								if global_padding is not None:
										if global_padding.upper() in self.supported_padding:
												A					       = global_padding.upper()
										else:
												raise ValueError(f'Padding strategy {global_padding} not supported'		)
								A					       = num_channels
								A					       = embedding_size
								A					       = hidden_sizes
								A					       = depths
								A					       = layer_type
								A					       = hidden_act
								A					       = global_padding
								A					       = num_groups
								A					       = drop_path_rate
								A					       = embedding_dynamic_padding
								A					       = output_stride
								A					       = width_factor

								A					       = ['stem'] + [f'stage{idx}' for idx in range(1			,			len(_lowercase		) + 1		)]
								A       , A					       = get_aligned_output_features_output_indices(
								    out_features=_lowercase			,			out_indices=_lowercase			,			stage_names=self.stage_names		)





