The Traveling Salesman Problem (TSP) is a classic optimization challenge that seeks the shortest possible route for a salesman to visit each city in a list exactly once and return to the origin city. 
We will use the POMO (Policy Optimization with Multiple Optima) reinforcement learning algorithm to solve this problem. 
Your task is to find a `heuristics` function for the POMO algorithm. This function will generate the attention bias matrix for the POMO algorithm's neural network. 
Your goal is to minimize the objective, which is the average test tour distances for the salesman (called "score" or "objective" of solution).