






"""simple docstring"""



import qiskit

def  _snake_case				(     lowerCamelCase__	:    int				,						lowerCamelCase__	:    int  )				->	qiskit.result.counts.Counts:
							lowerCamelCase_       :							List[Any]									=qiskit.Aer.get_backend("aer_simulator"  )

							lowerCamelCase_       :							Optional[int]									=qiskit.QuantumCircuit(4				,						2  )
							# encode inputs in qubits 0 and 1
							if bita == 1:
														qc_ha.x(0  )
							if bita == 1:
														qc_ha.x(1  )
							qc_ha.barrier()

							# use cnots to write XOR of the inputs on qubit2
							qc_ha.cx(0				,						2  )
							qc_ha.cx(1				,						2  )

							# use ccx / toffoli gate to write AND of the inputs on qubit3
							qc_ha.ccx(0				,						1				,						3  )
							qc_ha.barrier()

							# extract outputs
							qc_ha.measure(2				,						0  )  # extract XOR value
							qc_ha.measure(3				,						1  )  # extract AND value

							# Execute the circuit on the qasm simulator
							lowerCamelCase_       :							Dict									=qiskit.execute(_UpperCamelCase				,						_UpperCamelCase				,						shots=1_000  )

							# Return the histogram data of the results of the experiment
							return job.result().get_counts(_UpperCamelCase  )


if __name__ == "__main__":
						A__       :				Dict 					=					half_adder(1, 1)
						print(f'Half Adder Output Qubit Counts: {counts}')







"""simple docstring"""






from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
							if not (is_transformers_available() and is_torch_available()):
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							from ...utils.dummy_torch_and_transformers_objects import (
							    ImageTextPipelineOutput,
							    UniDiffuserPipeline,
							)
else:
							from .modeling_text_decoder import UniDiffuserTextDecoder
							from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
							from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline
