Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Onnx GPU export error #3837

Closed
SkanderMarsit opened this issue Jun 30, 2021 · 3 comments
Closed

Onnx GPU export error #3837

SkanderMarsit opened this issue Jun 30, 2021 · 3 comments
Labels
bug Something isn't working Stale

Comments

@SkanderMarsit
Copy link

Hello,

I'm having an issue exporting my trained model to ONNX on GPU.

The error is the following:
ONNX: export failure: Input, output and indices must be on the current device
after I run:
python3 export.py --weights ../best.pt --include onnx --device 0.
My code is up-to-date with the current master.
I have tried adding model.model[-1].export = True, but it did't resolve the problem.

I'm grateful for your help.

@SkanderMarsit SkanderMarsit added the bug Something isn't working label Jun 30, 2021
@github-actions
Copy link
Contributor

github-actions bot commented Jun 30, 2021

👋 Hello @SkanderMarsit, 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://www.ultralytics.com or email Glenn Jocher at glenn.jocher@ultralytics.com.

Requirements

Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run:

$ pip install -r requirements.txt

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):

Status

CI CPU testing

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), testing (test.py), inference (detect.py) and export (export.py) on MacOS, Windows, and Ubuntu every 24 hours and on every commit.

@glenn-jocher
Copy link
Member

@SkanderMarsit not all arguments are compatible during export. For ONNX please export on the default device (CPU).

@github-actions
Copy link
Contributor

github-actions bot commented Jul 31, 2021

👋 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.

Access additional YOLOv5 🚀 resources:

Access additional Ultralytics ⚡ resources:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐!

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
bug Something isn't working Stale
Projects
None yet
Development

No branches or pull requests

2 participants