





from __future__ import annotations

from math import pow, sqrt

def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				if (resistance, reactance, impedance).count(0 ) != 1:
								raise ValueError('One and only one argument must be 0' )
				if resistance == 0:
								return {"resistance": sqrt(pow(__lowerCAmelCase	,			2 ) - pow(__lowerCAmelCase	,			2 ) )}
				elif reactance == 0:
								return {"reactance": sqrt(pow(__lowerCAmelCase	,			2 ) - pow(__lowerCAmelCase	,			2 ) )}
				elif impedance == 0:
								return {"impedance": sqrt(pow(__lowerCAmelCase	,			2 ) + pow(__lowerCAmelCase	,			2 ) )}
				else:
								raise ValueError('Exactly one argument must be 0' )


if __name__ == "__main__":
		import doctest

		doctest.testmod()













lowercase_		:				Tuple				=						'''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

lowercase_		:				Optional[int]				=						[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
lowercase_		:				str				=						{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}






