ClearML integration removes the best checkpoint after uploading to the server

[kecsap]

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YOLOv5 Component

Integrations

Bug

YOLOv5 Git is up-to-date.
After configuring a local ClearML server, everything works fine, but the integration removes the uploaded best checkpoint file (best.pt) from runs/train/expXX/weights/ after the training is finished and it is uploaded to the server.

Environment

Ubuntu 20.04

Minimal Reproducible Example

No response

Additional

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• Yes I'd like to help by submitting a PR!

[github-actions]

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[glenn-jocher]

@thepycoder is the logging code deleting local checkpoints on upload?

[Denizzje]

Oh... so this might explain why I have not seen any best.pt at all having trained with various model sizes from YoloV5 v6.2. I geniunely thought something was changed from 6.1 to 6.2 (we use the fixed releases for training due to some modifications in training code). However I also enabled clearML when v6.2 got released. but to their hosted service for now instead of local server. None of my trained models had a best.pt in the weights folder after training. Looking at the ClearML artificats of each run, I do see them being there now.

[glenn-jocher]

@Denizzje no, the only reason best.pt would be missing is if you trained with --nosave or --noval.

[kecsap]

Just running the bleeding-edge master now.

ClearML installed:

$ python3 train.py --img 640 --batch 124 --epochs 3 --data XXX.yaml --weights yolov5s.pt --freeze 10
train: weights=yolov5s.pt, cfg=, data=XXX.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=3, batch_size=124, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[10], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
...
3 epochs completed in 0.002 hours.
Optimizer stripped from runs/train/exp92/weights/last.pt, 14.8MB
Optimizer stripped from runs/train/exp92/weights/best.pt, 14.8MB
...
Validating runs/train/exp92/weights/best.pt...
...
Results saved to runs/train/exp92
2022-09-02 11:49:55,696 - clearml.Task - INFO - Waiting to finish uploads
2022-09-02 11:49:55,801 - clearml.Task - INFO - Completed model upload to http://X.X.X.X:8081/YOLOv5/training.XXX/models/best.pt
2022-09-02 11:50:01,036 - clearml.Task - INFO - Finished uploading

$ ls runs/train/exp92/weights/best.pt
ls: cannot access 'runs/train/exp92/weights/best.pt': No such file or directory

Repeating the same after pip3 uninstall clearml:

$ python3 train.py --img 640 --batch 124 --epochs 3 --data XXX.yaml --weights yolov5s.pt --freeze 10
train: weights=yolov5s.pt, cfg=, data=XXX.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=3, batch_size=124, imgsz=640, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train, name=exp, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[10], save_period=-1, seed=0, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
...
3 epochs completed in 0.002 hours.
Optimizer stripped from runs/train/exp93/weights/last.pt, 14.8MB
Optimizer stripped from runs/train/exp93/weights/best.pt, 14.8MB
...
Validating runs/train/exp93/weights/best.pt...
...
Results saved to runs/train/exp93

$ ls runs/train/exp93/weights/best.pt
runs/train/exp93/weights/best.pt

[glenn-jocher]

@kecsap thanks for the example!

@thepycoder per the example in #9251 (comment) it appears the ClearML integration is moving or deleting best.pt after training completes.

Can you try to reproduce and investigate a fix? Thanks!

[thepycoder]

Hey @kecsap,

Thank you so much for the reproducible example. That is very weird indeed. I'm looking into it!

For others that might have the issue: you can still retrieve your best model by going to the experiment webui and downloading it there or by using the sdk

task = Task.get_task(task_id='previously_executed_task')
 my_local_copy_of_the_previously_uploaded_artifact = task.artifacts["best"].get_local_copy()

Not at a computer right now, but will fix asap!

[thepycoder]

Hey @glenn-jocher, @kecsap

I opened a PR with a fix. Sorry for the inconvenience!

[yuyang3478]

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[glenn-jocher]

@kecsap good news 😃! Your original issue may now be fixed ✅ in PR #9265. To receive this update:

• Git – git pull from within your yolov5/ directory or git clone https://github.com/ultralytics/yolov5 again
• PyTorch Hub – Force-reload model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
• Notebooks – View updated notebooks
• Docker – sudo docker pull ultralytics/yolov5:latest to update your image

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!