I’m experimenting with variational classifier which I have trained and obtained the optimal parameters. I wanted to score my trained model on the IBMQ cloud service, the following code contains the predict function for a set of data:
def predict(X,y,params): predicted_labels = [np.sign(variational_classifier(params, x=x)) for x in X] return predicted_labels, accuracy(y,predicted_labels)
I’ve already experimented with the IBMQ experience on qiskit and you can send a list of compiled circuits to the cloud as usually the quantum processors would be able to take up to 75 experiments at once in a single job submission. Can I work with batched circuits modifying my code or am I constrained to score a single example for a IBMQ job?
Thanks you very much!