1. Severity of the issue: (select one)
None: I’m just curious or want clarification.
Low: Annoying but doesn’t hinder my work.
Medium: Significantly affects my productivity but can find a workaround.
High: Completely blocks me.
2. Environment:
- Ray version: 2.10
- Python version: 3.11.11
- OS: Ubuntu 24.04.2 LTS
- Cloud/Infrastructure: /
- Other libs/tools (if relevant): /
3. What happened vs. what you expected:
I’ve been training some models using Population-based training and all of the trials have reached the terminated state as they have reached the stop condition.
Is there a way to update the stop condition from the saved state and continue training? E. .g., my trials all reached 10 M steps, but I would like to extend the training to 20 M, without having to retrain everything.