PyTorch Installation Fails on Nvidia Jetson Orin Nano Dev Board

Issue Overview

Users are experiencing difficulties when attempting to install PyTorch on the Nvidia Jetson Orin Nano Dev Board, specifically with the 8GB version running JetPack 6. The primary symptom is an error message encountered during the import of the PyTorch library in Python, which states:

OSError: libmpi.so.40: cannot open shared object file: No such file or directory

This issue arises after executing the installation command for PyTorch, which is designed to download and install the appropriate binary wheel for the Jetson platform. The error indicates a missing shared library, suggesting that there may be dependencies that have not been met.

The problem occurs consistently during the setup phase when users try to import the library after installation. It has a significant impact on user experience, as it prevents users from utilizing PyTorch for their machine learning projects on the Jetson platform.

Possible Causes

• Missing Dependencies: The installation of PyTorch requires certain third-party libraries that may not be installed by default on the Jetson platform.

• Configuration Errors: Incorrect installation commands or parameters could lead to incomplete installations, resulting in missing files or libraries.

• Driver Issues: Incompatibilities between installed drivers and the required libraries for PyTorch could cause runtime errors.

• User Errors: Users may inadvertently skip necessary steps outlined in the installation documentation, leading to issues.

Troubleshooting Steps, Solutions & Fixes

1. Verify Installation Command:

   • Ensure that you are using the correct command to install PyTorch. The command provided in the forum discussion is:

     python3 -m pip install --no-cache https://developer.download.nvidia.com/compute/redist/jp/v60dp/pytorch/torch-2.2.0a0+81ea7a4.nv24.01-cp310-cp310-linux_aarch64.whl
     

2. Install Missing Dependencies:

   • Follow NVIDIA’s official guide for prerequisites and installation of dependencies required for PyTorch on Jetson platforms. This can be found in their documentation:
     • Installing PyTorch for Jetson Platform – NVIDIA Docs

3. Check for libmpi.so.40:

   • Verify if libmpi.so.40 is installed by running:

     ls /usr/lib/aarch64-linux-gnu/libmpi.so*
     

   • If it is missing, you can install it using:

     sudo apt-get install libopenmpi-dev
     

4. Reinstall PyTorch:

   • After ensuring all dependencies are met, attempt to reinstall PyTorch using the same command as before.

5. Test Import:

   • After installation, test importing PyTorch again:

     python3 -c "import torch; print(torch.__version__)"
     

6. Check Environment Variables:

   • Ensure that your environment variables are set correctly to include paths to installed libraries.

7. Consult Logs:

   • If issues persist, consult system logs for additional error messages that might provide further insight into what is going wrong.

8. Community Support:

   • Engage with community forums or NVIDIA support if problems remain unresolved after following these steps.

By following these troubleshooting steps and ensuring all dependencies are installed correctly, users should be able to resolve the issue with installing and using PyTorch on their Nvidia Jetson Orin Nano Dev Board.