v0.2.0

What's Changed

This release includes several major updates to TorchFort, including:

• Enabling compilation of library with alternative compilers to NVHPC (e.g., GNU)
• Enabling model/RL system training and inference on CPU
• Enabling CPU-only builds without CUDA/NCCL
• New reinforcement learning features, including PPO algorithms and on-policy algorithms
• Improvements to build scripts

Breaking Changes

#14 enables placing and running models/RL systems on CPU. To enable this, an additional device argument was added to the model/system creation APIs (e.g., torchfort_model_create). Please refer to the documentation for more details.

PRs included in this release

• Enable support for complex gradient reduction in distributed cases. (#2)
• remove extraneous mpi call from cmake (#4)
• generalize cmake to build for different cuda archs (#7)
• remove hardcoded yaml-cpp path from CMakeLists.txt (#5)
• Build updates and improvements (#10)
• Update setup.cpp (#11)
• merging rl changes ( #13)
• Enable model training/inference on CPU or GPU devices. Enabling usage of alternative compilers to NVHPC, (#14)
• Tkurth/rl ppo (#12)
• Tkurth/rl tests (#15)
• Add train and inference functions for 5d Fortran arrays. (#17)
• Fix interface issues in Fortran module with gfortran. (#18)
• Enable builds without CUDA/GPU support (#19)
• Fixing up documentation. (#20)
• 0.2.0 release (#21)

Full Changelog: v0.1.0...v0.2.0