π Summary
Ultralytics v8.4.30 is a focused stability release that fixes and hardens training resume behavior, making interrupted training runs much more reliable πβ .
π Key Changes
- Main update (PR #24027 by @glenn-jocher): Refactored resume logic in
trainer.pyto correctly restore training arguments fromlast.ptearlier in the resume flow. - Better checkpoint arg handling: Resume now loads checkpoint config immediately and rebuilds runtime args from it more consistently.
- Safer dataset fallback: If the dataset path stored in a checkpoint is invalid, Ultralytics now falls back to the current
dataargument instead of failing unexpectedly. - Override support preserved: Users can still override practical resume-time settings like
imgsz,batch,device,workers,cache,freeze,val, andplots(plus related options). - Clear augmentation warning retained: If custom Albumentations were used before, a warning reminds users to pass
augmentationsagain when resuming, since they canβt be auto-restored exactly. - Version bump: Package updated from
8.4.29β8.4.30.
π― Purpose & Impact
- Purpose: Fix failing resume scenarios and make checkpoint restoration more robust after interruptions/crashes. π οΈ
- For users training large models: Fewer resume-related surprises, especially in long-running jobs on cloud/GPU servers. π
- For teams/pipelines: More predictable restart behavior in automated training workflows (CI/CD, scheduled jobs, preemptible instances). π€
- No new model architecture/features in this tag: This release is about reliability and continuity, not new YOLO model capabilities. π
What's Changed
ultralytics 8.4.30Fix training resume by @glenn-jocher in #24027
Full Changelog: v8.4.29...v8.4.30