Resolving ImportError: Could Not Find cudart64_100.dll in Python

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Understanding the context and the solution to this problem is crucial for Python developers who leverage GPU for heavy computational tasks. Here’s a step-by-step guide to resolve this issue.

Why does the ImportError occur?

CUDA Toolkit not installed: The CUDA toolkit might not be installed on your system.

Incorrect version: Your application may require a specific version of CUDA, and you'd need the corresponding DLL files.

How to Resolve the Error

Install the Correct CUDA Toolkit Version

Download and install the CUDA toolkit from the official NVIDIA website.

Follow the installation instructions carefully.

Verify the Installation Path

Ensure the installed CUDA directories are included in your system’s PATH. Typically, the necessary directories to add include C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.0\bin.

Go to System Properties > Environment Variables.

Under System variables, find the Path variable and click Edit.

Add the path to the CUDA bin directory if it’s not already listed.

Check for Compatibility

Ensure the libraries you're using are compatible with the installed version of the CUDA toolkit. You might need to update or downgrade your libraries or the CUDA toolkit as needed.

Python Environment Issues

If you’re using a virtual environment, make sure it's recognizing the CUDA libraries. Sometimes, recreating the virtual environment can resolve such issues.

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Check for CUDNN

Besides CUDA, some applications also require CUDNN (a GPU-accelerated library for deep neural networks, also from NVIDIA). Ensure that CUDNN is correctly installed and the paths are set up correctly.

Conclusion

Happy GPU computing with Python!