

from __future__ import annotations




def 					_lowercase     (				a_				:					list[float]				)				->	float:




					'''simple docstring'''







					__magic_name__							=    0.00
					__magic_name__							=    0
					for resistor in resistors:
										if resistor <= 0:
															__magic_name__							=    F'Resistor at index {index} has a negative or zero value!'
															raise ValueError(a_				)
										first_sum += 1 / float(a_				)
										index += 1
					return 1 / first_sum




def 					_lowercase     (				a_				:					list[float]				)				->	float:




					'''simple docstring'''







					__magic_name__							=    0.00
					__magic_name__							=    0
					for resistor in resistors:
										sum_r += resistor
										if resistor < 0:
															__magic_name__							=    F'Resistor at index {index} has a negative value!'
															raise ValueError(a_				)
										index += 1
					return sum_r


if __name__ == "__main__":
						import doctest

						doctest.testmod()





from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A__						=							{"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__						=							[
						    "VAN_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "VanForImageClassification",
						    "VanModel",
						    "VanPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_van import (
												    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
												    VanForImageClassification,
												    VanModel,
												    VanPreTrainedModel,
												)

else:
						import sys

						A__						=							_LazyModule(__name__, globals()["__file__"], _import_structure)




