Can’t install nvidia-tensorrt

Issue Overview

Users are experiencing difficulties installing the nvidia-tensorrt package on the Nvidia Jetson Orin Nano Dev board. The primary symptoms include error messages during installation attempts via pip, specifically indicating that the package is a placeholder on the PyPI repository and must be installed through the NVIDIA Python Package Index.

The context of the issue arises when users attempt to run the command:

pip3 install nvidia-tensorrt

This results in an error message stating that the installation is unsuccessful due to a failure in generating package metadata. Users have reported using Ubuntu 20.04, CUDA version 11.4, and Jetpack version 5.1.1, leading to confusion regarding compatibility and installation procedures.

The problem appears to be consistent among users attempting similar installations, significantly impacting their ability to utilize TensorRT for deep learning applications on their Jetson Orin Nano devices.

Possible Causes

• Incorrect Package Source: The error message indicates that the package is only a placeholder on PyPI and should be installed from NVIDIA’s repository.

• Version Conflicts: Users may be facing compatibility issues between the installed versions of CUDA, Python, and Jetpack. The presence of TensorRT version 5.1.1 in some outputs suggests potential mismatches.

• Installation Method: Users attempting to install via pip instead of apt may encounter issues due to incorrect or outdated package links.

• Misconfiguration: There may be configuration errors related to environment variables or Python paths that prevent successful installation.

• Software Bugs: There could be bugs within the installation scripts or conflicts with existing packages on the system.

Troubleshooting Steps, Solutions & Fixes

1. Verify Compatibility:

   • Check the compatibility of your hardware and software versions:

     head -n 1 /etc/nv_tegra_release
     

   • Ensure you are using Jetson Orin Nano with compatible versions of Ubuntu, CUDA, and Jetpack.

2. Install Using APT:

   • Instead of using pip, install TensorRT via apt:

     sudo apt install python3-libnvinfer*
     

   • This method is recommended as it ensures you are getting the correct versions from NVIDIA’s repository.

3. Check Installed Versions:

   • Verify installed versions of TensorRT and other related packages:

     apt show nvidia-tensorrt
     

   • Ensure that the output matches expected versions for your setup.

4. Remove Conflicting Packages:

   • If there are conflicting installations (e.g., multiple versions), consider removing them before reinstalling:

     sudo apt remove python3-libnvinfer*
     

5. Install NVIDIA Python Package Index:

   • If you still prefer using pip for other packages, first install NVIDIA’s Python Package Index:

     pip install nvidia-pyindex
     

   • Then try installing TensorRT again:

     pip install nvidia-tensorrt
     

6. Check Environment Variables:

   • Ensure that your environment variables are correctly set up for Python and CUDA paths.

7. Consult Documentation:

   • Refer to NVIDIA’s official documentation for TensorRT installation guidelines specific to Jetson devices.

8. Reboot and Retry:

   • After making changes or installations, reboot your device to ensure all settings take effect.

9. Community Support:

   • If issues persist, consider reaching out to community forums or NVIDIA support for further assistance.

By following these steps, users should be able to resolve their installation issues with nvidia-tensorrt on their Nvidia Jetson Orin Nano Dev board effectively.