Hello

I have a Hybrid (classical - quantum) model for classification:

*1st* layer is a classical layer with **6-neurons**

*2nd* layer is a standard quantum node with **6-qubits**

*3d* decision layer is a **2-neuron** classical layer with a sigmoid function

The Quantum node is the same as in the tutorial “https://pennylane.ai/qml/demos/tutorial_qnn_module_tf.html” but with 6 qubits.

It works fine but i would expect it not to work. Instead it makes sense to insert a classical layer of 6-neurons prior to the final decision layer.

My question is, should the output dimensions of the Qnode match the dimensions of the next classical layer? and if there is a mismatch how pennylane deals with it? thank you very much in advance!!!