embedding of that class such that when we do comparisons we're comparing at a class level rather than at the example level and this is exactly what prototypical networks does so they embed each of the data points for a given class such as the class corresponding to green blue or orange I average these to compute a prototype shown as CK and then make predictions based off of embedding the test data point X test and comparing it to each of the prototypes and what this looks like is we simply measure the distance acts between each of the