Celery logger stops working using torch.hub.load

[arjitkatare]

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YOLOv5 Component

PyTorch Hub

Bug

For some reasons, while using torch.hub.load in celery worker, logger is getting shutdown. By specifying v6.0 in repo_or_dir, issue seems to be resolved

Environment

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Minimal Reproducible Example

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Additional

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Are you willing to submit a PR?

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

[github-actions]

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[glenn-jocher]

@arjitkatare 👋 hi, thanks for letting us know about this possible problem with YOLOv5 🚀. We've created a few short guidelines below to help users provide what we need in order to get started investigating a possible problem.

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[github-actions]

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

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[JonathanSamelson]

I ran into the same issue with my own loggers after updating PyTorch to 1.10 (from 1.7.1).

The problem comes from this line:
self.net = torch.hub.load('ultralytics/yolov5', 'custom', path=self.model_path, verbose=False)

In this case, the output of my script is as follows:

2022-03-11 17:42:03 pluton aptitude-toolbox[22744] INFO Model type YOLO selected.
YOLOv5  2022-1-12 torch 1.10.2+cu113 CUDA:0 (GeForce GTX 1080 Ti, 11264MiB)

Fusing layers...
Model Summary: 213 layers, 7039792 parameters, 0 gradients
Adding AutoShape...
Detector init duration = 4.6338949000000005s
Model type SORT selected.
Tracker init duration = 0.019383399999999718s

Then, I don't have any output from my loggers anymore.

Whereas when adding a tag such as v6.0:
self.net = torch.hub.load('ultralytics/yolov5:v6.0', 'custom', path=self.model_path, verbose=False)

My loggers are working and don't stop:

2022-03-11 17:46:15 pluton aptitude-toolbox[12680] INFO Model type YOLO selected.
2022-03-11 17:46:19 pluton aptitude-toolbox[12680] INFO Detector init duration = 4.442983099999999s
2022-03-11 17:46:19 pluton aptitude-toolbox[12680] INFO Model type SORT selected.
2022-03-11 17:46:19 pluton aptitude-toolbox[12680] INFO Tracker init duration = 0.019554799999999872s
.... [After the process ends] ...
2022-03-11 17:46:21 pluton aptitude-toolbox[12680] INFO Average FPS: 12.473039525066566
2022-03-11 17:46:21 pluton aptitude-toolbox[12680] INFO Average FPS w/o read time: 13.190384737142026

As you can see, I still have the details provided by my logger in the latter case.

Also, using the latest tag (v6.1) give me another error, which is not related I think:
Exception: path is on mount 'C:', start on mount 'E:'. Cache may be out of date, try force_reload=True or see https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading for help.
I tried using force_reload, the result is the same.

[glenn-jocher]

@JonathanSamelson regarding the loggers, not sure what the problem could be. The current logging code is here, with LOGGER imported in various places:

yolov5/utils/general.py

Lines 77 to 88 in b94b59e

	def set_logging(name=None, verbose=VERBOSE):
	# Sets level and returns logger
	if is_kaggle():
	for h in logging.root.handlers:
	logging.root.removeHandler(h) # remove all handlers associated with the root logger object
	rank = int(os.getenv('RANK', -1)) # rank in world for Multi-GPU trainings
	logging.basicConfig(format="%(message)s", level=logging.INFO if (verbose and rank in (-1, 0)) else logging.WARNING)
	return logging.getLogger(name)
	LOGGER = set_logging('yolov5') # define globally (used in train.py, val.py, detect.py, etc.)

Regarding the PyTorch v6.1 PyTorch Hub usage this works correctly for me, I'm not able to reproduce any errors:

[JonathanSamelson]

@glenn-jocher I think the difference in the format is caused by this line:

logging.basicConfig(format="%(message)s", level=logging.INFO if (verbose and rank in (-1, 0)) else logging.WARNING)

I think it causes the logger to change the format for all loggers instead of only yolov5 logger.

And actually I was wrong in my previous message, the logger does not stop working but the level of the logger changes to INFO so the DEBUG message are filtered.

[glenn-jocher]

@JonathanSamelson ok got it. If you have a fix in mind can you please submit a PR? Thanks!

[JonathanSamelson]

@glenn-jocher At the moment, I don't. I'm using kind of the same lines in my project...
I understand it does not matter until it becomes an underlying project.

[glenn-jocher]

@arjitkatare @JonathanSamelson good news 😃! Your original issue may now be fixed ✅ in PR #7296 by @maxstrobel.

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 🚀!