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: 2.48.0
- Python version: 3.11
- OS: Ubuntu 22.04
- Cloud/Infrastructure: Determined AI
- Other libs/tools (if relevant):
3. What happened vs. what you expected:
- Expected: I can configure log dir in ray trainv2
- Actual: ray always keep log files in temp dir, after my container was killed, everything gone. That really hinder me from debugging.
when i migrate from trainv1 to v2, everything changed, it really annoying for not saving progress.csv and results.json.
Is there a mature solution that lets me use trainv2 and save my log efficiently? Includes print information, floating free metrics, and so on