Run main_rnet.py with the code at the end of the file main_rnet.py

1. Training: set value n in settings to be the number of bidders; set num_bidders in train_regretnet() as well as in settings.py, set distribution d. Can also set your own network shape in train_regretnet() function. Run main_rnet.py with only appropriately set train_regretnet() function. 

2. Evaluation: set value n in settings to be the number of bidders; set num_bidders, distribution, network shape, and checkpoint_path to the ones corresponding to the checkpoint you want to evaluate. Run main_rnet.py with only appropriately set eval_regretnet_bs() function. 

3. Verifying monotonicity: use regretNet_verifier/verifier_rnet.py, set num_bidders, network shape, and checkpoint_path to the ones corresponding to the checkpoint you want to verify. See regretNet_verifier/README for details. 

