

from __future__ import annotations

from math import pi






def        UpperCamelCase_(							_snake_case   :  float       ,     _snake_case   :  float       ,     _snake_case   :  float	):




			"""simple docstring"""






			if (inductance, frequency, reactance).count(0	) != 1:
						raise ValueError('One and only one argument must be 0'	)
			if inductance < 0:
						raise ValueError('Inductance cannot be negative'	)
			if frequency < 0:
						raise ValueError('Frequency cannot be negative'	)
			if reactance < 0:
						raise ValueError('Inductive reactance cannot be negative'	)
			if inductance == 0:
						return {"inductance": reactance / (2 * pi * frequency)}
			elif frequency == 0:
						return {"frequency": reactance / (2 * pi * inductance)}
			elif reactance == 0:
						return {"reactance": 2 * pi * frequency * inductance}
			else:
						raise ValueError('Exactly one argument must be 0'	)


if __name__ == "__main__":
						import doctest

						doctest.testmod()









_lowerCAmelCase					:			Optional[int]  				=			"\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

_lowerCAmelCase					:			Tuple  				=			[{"type": "code", "content": INSTALL_CONTENT}]
_lowerCAmelCase					:			Optional[int]  				=			{
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}






