I want to know how QNode is learning and calculating gradient in the below link https://pennylane.ai/qml/demos/tutorial_qnn_module_tf.html
Is this QNode learning calculating gradient on the principle of variational classifier?
QNode object is transformed to a Keras layer by using
qml.qnn.KerasLayer(qnode, weight_shapes, output_dim=n_qubits) it creates a
TensorFlow compatible tape and then the model is trained with the Keras SGD optimizer. The
QNode comes with a specific
diff_method=best which will be used to evaluate the gradient in the background for the given device. You can find more information about
QNode in the documentation here.
Feel free to ask more questions if needed!