I’ve been surveying the Ray documentation and examples on its GitHub page for a while to find an answer to do this, but can’t seem to find a solution.
I’m training multiple trials(
num_samples parameter in
tune.run) of PPO with Tune’s PBT and would like to get tensorboard and csv log files of some simulator-related custom metrics made during training.
Let’s say I’m running 10 samples. I’d like to know the custom_metric values each sample outputs after every episode while training.
The issues I’m facing are:
- There seems to be no method to access the sample indices such as 0~9 (since there are 10 samples), not the worker_index. Each sample uses multiple RolloutWorkers and I’d like to log the average of the custom metrics after each iteration.
- I’ve read the
DefaultCallbacksAPI and its example. This callback class is only “called at points during policy evaluation” as the documentation states, which is not what I want. I’m not using the evaluation option here.
- However, in case I do use evaluation in near future, I would like to know how to access/mutate the
episode (MultiAgentEpisode)object shown in the example. The example ray/custom_metrics_and_callbacks.py at master · ray-project/ray · GitHub uses
episode.custom_metrics, etc. How do I access/use these???
Thanks for any help.