Process defunct at DDP training #4414
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👋 Hello @yukkyo, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution. If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available. For business inquiries or professional support requests please visit https://ultralytics.com or email Glenn Jocher at glenn.jocher@ultralytics.com. RequirementsPython>=3.6.0 with all requirements.txt installed including PyTorch>=1.7. To get started: $ git clone https://github.com/ultralytics/yolov5
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@yukkyo good news 😃! Your original issue may now be fixed ✅ in PR #4422. This PR updates the DDP process group, and was verified over 3 epochs of COCO training with 4x A100 DDP NCCL on EC2 P4d instance with official Docker image and CUDA 11.1 pip install from https://pytorch.org/get-started/locally/ d=yolov5 && git clone https://github.com/ultralytics/yolov5 -b master $d && cd $d
python -m torch.distributed.launch --nproc_per_node 4 --master_port 1 train.py --data coco.yaml --batch 64 --weights '' --project study --cfg yolov5l.yaml --epochs 300 --name yolov5l-1280 --img 1280 --linear --device 0,1,2,3
python -m torch.distributed.launch --nproc_per_node 4 --master_port 2 train.py --data coco.yaml --batch 64 --weights '' --project study --cfg yolov5l.yaml --epochs 300 --name yolov5l-1280 --img 1280 --linear --device 4,5,6,7To receive this update:
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 🚀! |
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@glenn-jocher |
The DDP training did not finish correctly. This did not happen with Single GPU training.
0. Environment
d9f23ed6d65e985c07e9ef0ec77d476dd14e2b26)1. Trying command
python -m torch.distributed.run \ --nproc_per_node 2 train.py \ --batch 48 \ --workers 16 \ --data ../../../input/nfl_yolov5_fold_0_5.yaml \ --weights yolov5x.pt \ --single-cls \ --img 704 \ --epochs 1 \ --device 0,12. Output
Results on the way
It stopped in the following state.
It also kept catching the GPU 0. (But not used)
nvidia-smi
And I got below result when input
<Ctrl + C>.Do you know how to deal with this?
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