The function that the perceptron is learning will be a polynomial of N variables, where N is the number of nodes in the perceptron. The coefficients of the polynomial are generated randomly (see the function init). We can use these coefficients to generate a value with a single reduction operation, and then compare the resulting value to 0. If the value is greater than or equal to 0, the desired output is 1; otherwise, the desired output is 0. You are welcome to generate different examples, if you wish.