We’ve been using TensorRT for several years with different neural networks on different platforms, jetson (xavier), desktop (2080), server (T4), …
We’ve just started supporting Jetson Orin with our current models and we have found an odd issue.
Some networks are returning different values on Jetson Orin AGX with JetPack 5.1
I have created an example using pose estimation to reproduce the problem, you can download the code from the following link:
Steps to reproduce the problem:
1 - Install onnxruntime
$> pip3 install onnxruntime
2 - Build plan file using trtexec
$> ./trtexec_pose.sh build
3 - Run plan file and save outputs
$> ./trtexec_pose.sh infer
4 - Get results for the same input using onnxruntime
$> python3 onnxruntime_pose.py
5 - Finally compare trtexec and onnxruntime results
$> python3 check_results.py
Same steps on Jetson Xavier AGX (JetPack 4.5) or Tesla T4 or RTX 2080ti … give equivalent results when we use onnxruntime or tensorrt.