





import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute






def   lowerCamelCase_		(       _UpperCamelCase = np.pi / 2				,       _UpperCamelCase = np.pi / 2				,       _UpperCamelCase = np.pi / 2				)	->		qiskit.result.counts.Counts:






				"""simple docstring"""


				snake_case_			    =						QuantumRegister(3				,       '''qr'''				)  # Define the number of quantum bits
				snake_case_			    =						ClassicalRegister(1				,       '''cr'''				)  # Define the number of classical bits

				snake_case_			    =						QuantumCircuit(lowerCamelCase__				,       lowerCamelCase__				)  # Define the quantum circuit.

				# Build the circuit
				quantum_circuit.u(lowerCamelCase__				,       lowerCamelCase__				,       lowerCamelCase__				,       0				)  # Quantum State to teleport
				quantum_circuit.h(1				)  # add hadamard gate
				quantum_circuit.cx(
				    1				,       2				)  # add control gate with qubit 1 as control and 2 as target.
				quantum_circuit.cx(0				,       1				)
				quantum_circuit.h(0				)
				quantum_circuit.cz(0				,       2				)  # add control z gate.
				quantum_circuit.cx(1				,       2				)

				quantum_circuit.measure([2]				,       [0]				)  # measure the qubit.

				# Simulate the circuit using qasm simulator
				snake_case_			    =						Aer.get_backend('''aer_simulator'''				)
				snake_case_			    =						execute(lowerCamelCase__				,       lowerCamelCase__				,       shots=1_000				)

				return job.result().get_counts(lowerCamelCase__				)


if __name__ == "__main__":
	print(
	    '''Total count for teleported state is: '''
	    F'''{quantum_teleportation(np.pi/2, np.pi/2, np.pi/2)}'''
	)







import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


lowerCAmelCase_												=       logging.get_logger(__name__)



class       __lowerCAmelCase (    _a  ):






			def __init__(self      ,							*__magic_name__      ,							**__magic_name__					)  ->     None:


							'''simple docstring'''



							warnings.warn(
							    '''The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
							    ''' Please use MobileNetV2ImageProcessor instead.'''      ,							__magic_name__      ,							)
							super().__init__(*__magic_name__      ,							**__magic_name__					)
