Getting error while Converting to tensorRT about ultralytics HOT 5 CLOSED

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Install

Pip install the ultralytics package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.

pip install ultralytics

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YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

• 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

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from ultralytics.

When I get errors like that from TensorRT it is typically because some layer is not quantizable. Yolov9 might have added some layer which is not quantizable. What TensorRT version are you on?

from ultralytics.

It looks like you're encountering a compatibility issue with TensorRT and the model's architecture. The error message Unsupported SM: 0x900 suggests that your GPU's compute capability might not be supported by the TensorRT version you're using.

Could you confirm the GPU model you're using? Also, updating to the latest TensorRT version might help if your GPU is relatively new. This can often resolve issues with unsupported layers or features in newer models like YOLOv9.

from ultralytics.

@glenn-jocher it turns out I have a problem with the instance I was using for inference.
however I have resolved it my problem by changing to a different instance.
However thanks your support

from ultralytics.

Glad to hear you resolved the issue by switching instances! If you have any more questions or run into other issues, feel free to reach out. Happy coding! 🚀

from ultralytics.