ImportError: libcublas.so.10: Cannot Open Shared Object File on Nvidia Jetson

Issue Overview

Users are encountering an ImportError related to libcublas.so.10 while attempting to build and run a ROS2 container on the Nvidia Jetson platform. The specific details of the issue include:

• Symptoms: The error message indicates that the system cannot find the shared object file libcublas.so.10, which is required for OpenCV operations within the Docker container.

• Context: The issue arises when executing the command:

  ./scripts/docker_build_ros.sh --distro humble
  

  This command is intended to build a Docker container for ROS2 using the Jetson Inference repository.

• Hardware/Software Specifications:

  • Environment: Nvidia Jetson device running JetPack (specific version not provided).
  • Python Version: 3.6
  • OpenCV Version: Related to the installation process.

• Frequency: This appears to be a consistent issue for users attempting to build ROS2 containers on their Jetson devices.

• Impact on User Experience: The inability to locate necessary libraries prevents users from successfully building and running their applications, significantly hindering development efforts.

Possible Causes

Several factors may contribute to this ImportError:

• Missing Library: The specific version of libcublas.so.10 may not be installed on the system, or it may not be correctly linked in the expected directories.

• Incorrect Docker Configuration: If the default Docker runtime is not set to NVIDIA, it may lead to issues with accessing GPU-related libraries during container execution.

• Incompatible Software Versions: The installed versions of CUDA, cuDNN, or TensorRT may not match the requirements of OpenCV or other libraries being used.

• User Errors During Setup: Misconfigurations during the installation or setup process can lead to missing dependencies or incorrect paths.

Troubleshooting Steps, Solutions & Fixes

To resolve the ImportError related to libcublas.so.10, follow these troubleshooting steps:

1. Verify Library Installation:

   • Check if libcublas.so.10 is installed on your system:

     locate libcublas.so
     

   • If it is missing, install or update CUDA Toolkit which includes cuBLAS:

     sudo apt-get install cuda-toolkit-<version>
     

2. Set Default Docker Runtime to NVIDIA:

   • Ensure that your Docker is configured to use NVIDIA as the default runtime. You can do this by editing the Docker configuration file:

     sudo nano /etc/docker/daemon.json
     

   • Add or modify the following lines:

     {
       "default-runtime": "nvidia",
       "runtimes": {
         "nvidia": {
           "path": "nvidia-container-runtime",
           "runtimeArgs": []
         }
       }
     }
     

   • Restart Docker:

     sudo systemctl restart docker
     

3. Rebuild the Docker Container:

   • After ensuring that all dependencies are installed and configurations are correct, attempt to rebuild your ROS2 container again:

     ./scripts/docker_build_ros.sh --distro humble
     

4. Check for Compatibility Issues:

   • Verify that your versions of CUDA, cuDNN, and TensorRT are compatible with each other and with OpenCV. Refer to Nvidia’s documentation for version compatibility charts.

5. Consult Documentation and Community Resources:

   • Review Nvidia’s official documentation for setting up ROS2 containers and troubleshooting common issues.
   • Engage with community forums for additional insights from users who may have faced similar issues.

6. Unresolved Aspects:

   • Users may still encounter unique challenges based on their specific configurations or setups not covered in common solutions. Further investigation may be required if standard troubleshooting does not resolve the problem.

By following these steps, users should be able to troubleshoot and resolve issues related to ImportError: libcublas.so.10 while working with Docker containers on their Nvidia Jetson devices.