How to disable UserWarning: User provided device_type of 'cuda', but CUDA is not available and reduce output per epoch to a single line?.

[RRighart]

Search before asking

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

Question

I am running Yolov5 on my machine using CPU (there is no GPU). This is giving many warnings that CUDA is not available.
In addition, running a single epoch the logging is taking up many lines like the following output:

 Epoch   gpu_mem       box       obj       cls    labels  img_size
  0%|          | 0/180 [00:00<?, ?it/s]                                         /usr/local/lib/python3.8/dist-packages/torch/autocast_mode.py:141: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling
  warnings.warn('User provided device_type of \'cuda\', but CUDA is not available. Disabling')
       0/2        0G   0.08552    0.0316   0.01973         3       640:   1%|   /usr/local/lib/python3.8/dist-packages/torch/autocast_mode.py:141: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling
  warnings.warn('User provided device_type of \'cuda\', but CUDA is not available. Disabling')
       0/2        0G   0.08275   0.03398   0.02043         3       640:   1%|   /usr/local/lib/python3.8/dist-packages/torch/autocast_mode.py:141: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling
  warnings.warn('User provided device_type of \'cuda\', but CUDA is not available. Disabling')
       0/2        0G   0.06593    0.0328     0.017         2       640:   2%|▏  /usr/local/lib/python3.8/dist-packages/torch/autocast_mode.py:141: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling 

In Kaggle running with CPU this issue is not occurring, it is just taking a single line for each epoch.

Is there a setting where I can reduce this output to a single line per epoch, like in Kaggle?

Additional

No response

[github-actions]

👋 Hello @RRighart, 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]

TODO: try

warnings.filterwarnings(action='ignore', category=torch.jit.TracerWarning)  # suppress TracerWarning

[glenn-jocher]

@RRighart good news 😃! Your original issue may now be fixed ✅ in PR #6706. 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 🚀!

[ok-kewei]

I encountered the same error ".. but CUDA is not available...." and solved it by installing the nvidia driver.

1. sudo apt-get update
2. sudo apt-get install nvidia-driver-418 (depends on the model of your nvidia)