Order of Performing nested K-fold cross validation

I have been looking at the following tutorial on correct model validation:

 

I'm looking at the section on contamination through feature selection when doing K-fold cross validation. In the section on Accidental Contamination, near the bottom in example 3), it is suggesting to use nested K-fold validation to search for features in a similar way to that which is being suggested in example 2) for the choice of hyperparameters.

My question is: Is there any best practice around whether to do the nested k-fold validation for feature selection first, then to use the selected features for the nested validation on the hyperparameters, or vice versa? I am imagining it will be too computationally expensive to nest all 3 techniques within one another.

 

Can anyone advise on this?

Thank you