From GitHub issue #130 by @chMoussa:

Hello,

I want to write a CV classifier. To get probabilities in the context of binary classification,

we would need two expectation values. For instance, get the Fock probability of [0, 1] and [1, 0] outcomes and normalize like:`p0 = qml.expval.cv.NumberState(np.array([1, 0]), wires=[0, 1]) p1 = qml.expval.cv.NumberState(np.array([0, 1]), wires=[0, 1]) return p1 / (p0+p1 + 1e-10)`

However, I am not able to do so because :

`QuantumFunctionError: Each wire in the quantum circuit can only be measured once. TypeError: unsupported operand type(s) for +: 'NumberState' and 'NumberState'`

How can we do so currently?