Reinstallation and Troubleshooting

Oct 13, 2025 by thesweetdesigns.com 147 views

Introduction

WSL (Windows Subsystem for Linux) has become a popular choice for developers and data scientists to run Linux applications on Windows. Comfy is a WSL distribution that provides a comfortable and familiar Linux environment for users. However, as with any complex system, issues can arise when trying to install and run specific packages. In this article, we will explore the challenges of installing the Nunchaku package using WSL Comfy, both from a wheel and from source.

Environment Setup

Before diving into the issues, let's take a look at the environment setup. The user has installed WSL Comfy from Git, with CUDA 12.8 and other necessary packages installed and working. This setup provides a solid foundation for running complex applications like Nunchaku.

Installing from Wheel

The user attempts to install Nunchaku from a wheel using the huggingface (hf) package. However, this results in errors like the following:

lib/python3.12/site-packages/nunchaku/_C.cpython-312-x86_64-linux-gnu.so: undefined symbol: _ZN3c106DeviceC1ERKSs

This error suggests that there is a problem with the compiled C code, specifically with the nunchaku/_C.cpython-312-x86_64-linux-gnu.so file. The undefined symbol _ZN3c106DeviceC1ERKSs indicates that the compiler is unable to find the definition for this symbol.

Building from Source

Frustrated with the wheel installation, the user decides to build Nunchaku from source. This process involves running nvcc (the NVIDIA CUDA compiler) and compiling the kernels, which can be a time-consuming process. After 1 hour of compilation on a 5950X CPU, the user finally sees the following output:

Successfully built nunchaku
Installing collected packages: nunchaku
Successfully installed nunchaku-0.1.4+torch2.6

No errors are reported during the compilation process, which suggests that the build was successful.

Import Errors

Despite the successful compilation, the user still encounters import errors when trying to use Nunchaku in Comfy. The error message reads:

ImportError: cannot import name 'NunchakuFluxTransformer2dModel' from 'nunchaku' (unknown location)

This error suggests that there is a problem with the Python package installation or the import mechanism.

Reinstallation and Troubleshooting

The user attempts to reinstall Nunchaku and troubleshoot the issue, but no changes are observed. This suggests that the problem may be more complex and requires further investigation.

Conclusion

The experience of installing Nunchaku using WSL Comfy, both from a wheel and from source, highlights the challenges of working with complex systems. While the user was able to successfully compile the package from source, the import errors suggest that there may be issues with the Python package installation or the import mechanism. Further investigation and troubleshooting are necessary to resolve these issues and ensure a smooth installation process.

Troubleshooting Tips

For users who encounter similar issues, here are some troubleshooting tips:

Check the package installation: Ensure that the package is installed correctly and that there are no issues with the Python package installation.
Verify the import mechanism: Check the import mechanism to ensure that it is working correctly and that there are no issues with the import statements.
Reinstall the package: Attempt to reinstall the package to see if the issue is resolved.
Check for conflicts: Check for conflicts between packages or dependencies that may be causing the issue.

Introduction

In our previous article, we explored the challenges of installing Nunchaku using WSL Comfy, both from a wheel and from source. We discussed the issues encountered during the installation process and provided some troubleshooting tips. In this article, we will answer some frequently asked questions (FAQs) related to the installation of Nunchaku using WSL Comfy.

Q: What is WSL Comfy?

A: WSL Comfy is a WSL distribution that provides a comfortable and familiar Linux environment for users. It is designed to make it easy to install and run Linux applications on Windows.

Q: What is Nunchaku?

A: Nunchaku is a Python package that provides a set of tools for building and training deep learning models. It is designed to work with popular deep learning frameworks such as PyTorch and TensorFlow.

Q: Why am I getting import errors when trying to use Nunchaku in Comfy?

A: Import errors can occur when there is a problem with the Python package installation or the import mechanism. In the case of Nunchaku, the import errors may be caused by a conflict between packages or dependencies.

Q: How do I troubleshoot import errors in Comfy?

A: To troubleshoot import errors in Comfy, you can try the following:

Check the package installation: Ensure that the package is installed correctly and that there are no issues with the Python package installation.
Verify the import mechanism: Check the import mechanism to ensure that it is working correctly and that there are no issues with the import statements.
Reinstall the package: Attempt to reinstall the package to see if the issue is resolved.
Check for conflicts: Check for conflicts between packages or dependencies that may be causing the issue.

Q: Why is building Nunchaku from source taking so long?

A: Building Nunchaku from source can take a long time because it involves compiling the kernels using the NVIDIA CUDA compiler (nvcc). This process can be time-consuming, especially on slower hardware.

Q: Can I use Nunchaku with other deep learning frameworks?

A: Yes, Nunchaku is designed to work with popular deep learning frameworks such as PyTorch and TensorFlow. However, you may need to modify the code or use additional tools to work with other frameworks.

Q: Where can I find more information about Nunchaku and WSL Comfy?

A: You can find more information about Nunchaku and WSL Comfy on the following websites:

Nunchaku documentation: https://nunchaku.readthedocs.io/
WSL Comfy documentation: https://docs.microsoft.com/en-us/windows/wsl/comfy
NVIDIA CUDA documentation: https://docs.nvidia.com/cuda/

Conclusion

In this article, we answered some frequently asked questions (FAQs) related to the installation of Nunchaku using WSL Comfy. We provided some troubleshooting tips and information about Nunchaku and WSL Comfy. We hope this article has been helpful in resolving any issues you may have encountered during the installation process.