  A range of applications for automatic machine learning need the generation
process to be controllable. In this work, we propose a way to control the
output via a sequence of simple actions, that are called semantic code classes.
Finally, we present a semantic code classification task and discuss methods for
solving this problem on the Natural Language to Machine Learning (NL2ML)
dataset.
