



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase__     = {
    "configuration_upernet": ["UperNetConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase__     = [
           "UperNetForSemanticSegmentation",
           "UperNetPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_upernet import UperNetConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_upernet import UperNetForSemanticSegmentation, UperNetPreTrainedModel


else:
       import sys

       UpperCAmelCase__     = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





import qiskit





def 							A			(  _UpperCAmelCase       :     int							,     _UpperCAmelCase       :     int					)       ->				qiskit.result.counts.Counts:







			'''simple docstring'''
			_UpperCAmelCase	 =     qiskit.Aer.get_backend('aer_simulator'					)

			# Create a Quantum Circuit acting on the q register
			_UpperCAmelCase	 =     qiskit.QuantumCircuit(_UpperCAmelCase							,     _UpperCAmelCase					)

			# Apply X (NOT) Gate to Qubits 0 & 1
			circuit.x(0					)
			circuit.x(1					)

			# Map the quantum measurement to the classical bits
			circuit.measure([0, 1]							,     [0, 1]					)

			# Execute the circuit on the qasm simulator
			_UpperCAmelCase	 =     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__":
							UpperCAmelCase__     = single_qubit_measure(2, 2)
							print(f"""Total count for various states are: {counts}""")
