module 'signal' has no attribute 'SIGALRM' when training in dataset

[tongtongkunkun]

Search before asking

• I have searched the YOLOv5 issues and discussions and found no similar questions.

Question

this problem came to when I run in the window system.
the error as following:

module 'signal' has no attribute 'SIGALRM'

AutoAnchor: 5.67 anchors/target, 1.000 Best Possible Recall (BPR). Current anchors are a good fit to dataset
Image sizes 64 train, 64 val
Using 8 dataloader workers
Logging results to runs\train\exp13
Starting training for 100 epochs...

 Epoch   gpu_mem       box       obj       cls    labels  img_size

0%| | 0/127 [00:05<?, ?it/s]
Traceback (most recent call last):
File "D:\anacoda\anacoda-install\lib\site-packages\torch\utils\data\dataloader.py", line 872, in _try_get_data
data = self._data_queue.get(timeout=timeout)
File "D:\anacoda\anacoda-install\lib\queue.py", line 178, in get
raise Empty
_queue.Empty

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "E:/Machine_Learning/yolov5/yolov5-master/yolov5-master/train.py", line 643, in
main(opt)
File "E:/Machine_Learning/yolov5/yolov5-master/yolov5-master/train.py", line 539, in main
train(opt.hyp, opt, device, callbacks)
File "E:/Machine_Learning/yolov5/yolov5-master/yolov5-master/train.py", line 305, in train
for i, (imgs, targets, paths, _) in pbar: # batch -------------------------------------------------------------
File "D:\anacoda\anacoda-install\lib\site-packages\tqdm\std.py", line 1167, in iter
for obj in iterable:
File "E:\Machine_Learning\yolov5\yolov5-master\yolov5-master\utils\datasets.py", line 141, in iter
yield next(self.iterator)
File "D:\anacoda\anacoda-install\lib\site-packages\torch\utils\data\dataloader.py", line 435, in next
data = self._next_data()
File "D:\anacoda\anacoda-install\lib\site-packages\torch\utils\data\dataloader.py", line 1068, in _next_data
idx, data = self._get_data()
File "D:\anacoda\anacoda-install\lib\site-packages\torch\utils\data\dataloader.py", line 1024, in _get_data
success, data = self._try_get_data()
File "D:\anacoda\anacoda-install\lib\site-packages\torch\utils\data\dataloader.py", line 885, in _try_get_data
raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str)) from e
RuntimeError: DataLoader worker (pid(s) 2924, 11744, 6944, 11576, 8828, 17232, 5968, 5168) exited unexpectedly

Process finished with exit code 1

Additional

No response

[github-actions]

👋 Hello @tongtongkunkun, 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 support@ultralytics.com.

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.

[glenn-jocher]

@tongtongkunkun it appears you may have environment problems. Please ensure you meet all dependency requirements if you are attempting to run YOLOv5 locally. If in doubt, create a new virtual Python 3.9 environment, clone the latest repo (code changes daily), and pip install requirements.txt again from scratch.

💡 ProTip! Try one of our verified environments below if you are having trouble with your local environment.

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

Models and datasets download automatically from the latest YOLOv5 release when first requested.

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.

[yeshanliu]

#5395 (comment) Find 'plot_labels' and remove 'Timeout(30)' behind it.

[glenn-jocher]

@tongtongkunkun @yeshanliu good news 😃! Your original issue may now be fixed ✅ in PR #7013. This PR disables Timout using SIGALARM on Windows. 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 🚀!