How to use SMOTE in Stacking in SKLearn?
First question, whether to use SMOTE for the first or second of a stacked classifiers. Generally, SMOTE should be done before any classification since SMOTE gives the minority class an increased likelihood be being successfully learned. The first classifier should be given the most useful features. Another way to approach is looking for empirical evidence. Train models both ways and choose the ordering that performs betters.
Second question, SMOTE is only done on the training dataset. During prediction, only the data that is present is predicted. If you use imblearn's Pipeline, this automatically handled.