f90wrap
neural-fortran
| f90wrap | neural-fortran | |
|---|---|---|
| 2 | 3 | |
| 235 | 375 | |
| - | 2.9% | |
| 6.9 | 5.5 | |
| 8 days ago | 5 days ago | |
| Python | Fortran | |
| GNU Lesser General Public License v3.0 only | MIT License |
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f90wrap
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Any help or tips for Neural Networks on Computer Clusters
However, if you are writing numerical code in Fortran and want to be able to better interface it it with machine learning tools and methods, the number one thing I can recommend is to look into Fortran-based automatic differentiation tools. This will enable you to calculate exact derivatives of your code, which are useful to have for training and optimization loops. You can also look into f2py and f90wrap for generating Python wrappers for your Fortran codes, as well as Julia for hooking into it directly.
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Runtime communication Fortran <-> Python
When I looked into this a bit, I found f90wrap to have reasonable ergonomics and CMake support. If you haven’t seen it already, you might give it a shot.
neural-fortran
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Fortran 2023 has been published
A few more:
https://github.com/modern-fortran/neural-fortran (disclaimer, I originally created this one)
https://github.com/BerkeleyLab/inference-engine
https://git.exeter.ac.uk/hepplestone/athena
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Any help or tips for Neural Networks on Computer Clusters
check out this, it's not really a framework but good enough to start with
- PyTorch Fortran Bindings
What are some alternatives?
forpy - Forpy - use Python from Fortran
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
SixTrack - SixTrack – 6D Tracking Code
fpm - Fortran Package Manager (fpm)
Fortran-code-on-GitHub - Directory of Fortran codes on GitHub, arranged by topic
stdlib - Fortran Standard Library
julia - The Julia Programming Language
pytorch-fortran - Pytorch bindings for Fortran
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
WRF - The official repository for the Weather Research and Forecasting (WRF) model
ftl - The Fortran Template Library