Cvqnn_layers_all

PennyLane Help
2

Hi @Aigerim,

The following code from the CVNeuralNetLayers docs should help you.

shapes = CVNeuralNetLayers.shape(n_layers=2, n_wires=2)
weights = [np.random.random(shape) for shape in shapes]

def circuit():
  CVNeuralNetLayers(*weights, wires=[0, 1])
  return qml.expval(qml.X(0))

Please let me know if this solves your problem!