alexeedm/pytorch-fortran
Pytorch bindings for Fortran
This project helps Fortran HPC developers integrate PyTorch deep learning capabilities directly into their existing Fortran codebases. You can define a neural network model in Python, load it into Fortran, pass in Fortran arrays as input, run inference or training, and receive the output as native Fortran arrays. This allows Fortran developers to leverage PyTorch's optimized deep learning framework without rewriting their high-performance computing applications.
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Use this if you are a Fortran HPC developer who needs to incorporate deep learning models into your high-performance computing applications, performing tasks like inference or training, while keeping your core logic in Fortran.
Not ideal if you are primarily a Python deep learning developer and don't work with existing Fortran high-performance computing codes.
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Language
C++
License
MIT
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Last pushed
Jan 18, 2024
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