





'''simple docstring'''

import qiskit







def    a__							(							lowercase   :	int,   lowercase   :	int )						->						qiskit.result.counts.Counts:





     """simple docstring"""

     _UpperCamelCase							       =			qiskit.Aer.get_backend('''aer_simulator''' )

     _UpperCamelCase							       =			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
     _UpperCamelCase							       =			qiskit.execute(lowercase,   lowercase,   shots=1000 )

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


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










'''simple docstring'''

from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__		:     Tuple			=							{'configuration_mmbt': ['MMBTConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase__		:     int			=							['MMBTForClassification', 'MMBTModel', 'ModalEmbeddings']


if TYPE_CHECKING:
   from .configuration_mmbt import MMBTConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
   import sys

   lowercase__		:     List[Any]			=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



