To determine which model is used during testing

[yzhou-saic]

During testing, how can we determine the best model to be used ?
For example, to repeat the results on the KITTI leading board, how can you determine the model to be used ? Do you just use the last model when 120,000 iterations are finished ?

[kujason]

As with many other methods on the leaderboards, the network is trained on a private custom split of only the provided KITTI training data for better generalization. Our training procedure and hyperparameter selection is outlined in the paper, and the plot_ap.py script is provided to make it easier to select a good checkpoint, so feel free to experiment and see what works best for you.

[yzhou-saic]

But in order to repeat the results reported in the paper:
During testing (not validation), there is no way to use plot_ap.py
Do you just use the last model when 120,000 iterations are finished ?
Or do you pick up the same iteration which is the best on validation set ?