Hi everyone,

I found a confused problem about parameter shape when I use CVNeuralNetLayers:

```
dev = qml.device('strawberryfields.fock', wires=2, cutoff_dim=10)
def circuit(pars):
CVNeuralNetLayers(*pars, wires=range(2))
@qml.qnode(dev)
def quantum_neural_net(var, x1=None,x2=None):
qml.Displacement(x1, 0.0, wires=0)
qml.Displacement(x2, 0.0, wires=1)
circuit(var)
return qml.expval(qml.X(0))
init_pars=cvqnn_layers_all(n_layers=2, n_wires=2, seed= None)
result = [quantum_neural_net(init_pars, x1=xlo[0],x2=xlo[1]) for xlo in X]
#X is dataset with shape (# of samples, 2)
ValueError: could not broadcast input array from shape (2,1) into shape (2)
```

However, I tried number of wires 1,2,4 all return similar error. Only use 3 wires, it would work. I read the CVNeuralNetLayers documentation, I found the M =K when wires are 3.