Torch v1.12 fixes bug to train a model, but YoloV5 rejects the version.

[Exortions]

Search before asking

• I have searched the YOLOv5 issues and found no similar bug report.

YOLOv5 Component

Training

Bug

Recently, training in YOLOv5 would crash because of an error in PyTorch. (See this issue: pytorch/pytorch#74016)

PyTorch released a fix in version 1.12, but YOLOv5 doesn't train with this error:
requirements: torch!=1.12.0,>=1.7.0 not found and is required by YOLOv5, attempting auto-update...
It then downgrades PyTorch to v1.11.0, which once again crashes the training process when ran with it.

How can I get PyTorch v1.12 to run with YOLOv5?

Environment

• YOLO: YOLOv5 latest
• OS: Windows 11 (WSL)
• Python: 3.9.0

Minimal Reproducible Example

git clone https://github.com/ultralytics/yolov5
cd yolov5

pip install torch==1.12

python train.py --img 640 --batch 16 --epochs 10 --data coco128.yaml --weights yolov5s.pt --cache

Additional

No response

Are you willing to submit a PR?

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

[github-actions]

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Requirements

Python>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started:

git clone https://github.com/ultralytics/yolov5  # clone
cd yolov5
pip install -r requirements.txt  # install

Environments

YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

• Google Colab and Kaggle notebooks with free GPU:
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. See AWS Quickstart Guide
• Docker Image. See Docker Quickstart Guide

Status

If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training (train.py), validation (val.py), inference (detect.py) and export (export.py) on macOS, Windows, and Ubuntu every 24 hours and on every commit.

[equal-l2]

It seems that they intentionally exclude torch 1.12.0 because the version has a serious bug in multi-GPU environments.
See #8395 for the detail.

TL; DR: The only thing we users can do is wait for the new release of torch (1.12.1, presumably).

[glenn-jocher]

@Exortions @equal-l2 good news 😃! Your original issue may now be fixed ✅ in PR #8621. torch==1.12.0 installs are now allowed, and an assert torch!=1.12.0 has been inserted into a new smart_DDP() function. The Docker image is using torch nightly and trains DDP correctly.

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 🚀!

[Exortions]

Thank you so much!

[glenn-jocher]

@Exortions you're very welcome! 🎉 Kudos to the persevering and passionate YOLO community - and the incredible Ultralytics team who made this update possible. Please don't hesitate to reach out if you have any more questions or need further assistance. Good luck with your YOLOv5 adventures!