1. A computer-implemented method of training a machine-learning based datapath extraction tool, comprising: receiving a learning set of design patterns representing clusters of interconnected cells wherein each design pattern is designated as either datapath or non-datapath, by executing first instructions in a computer system; identifying cluster features in the design patterns, by executing second instructions in the computer system; applying one or more machine-learning models to the cluster features to selectively associate the features with either datapath logic or non-datapath logic, by executing third instructions in the computer system; and calibrating the one or more machine-learning models, by executing fourth instructions in the computer system.