OpenMM-Torch 1.4

This release fixes an issue with CUDA Graphs (#122) and support for Python 3.12 (#123).

This release can be installed from conda-forge:

conda install -c conda-forge openmm-torch=1.4

What's Changed

• Use the same stream as the OpenMM context when replaying a CUDA graph. by @RaulPPelaez in #122
• Use setuptools instead of distutils by @peastman in #123

Full Changelog: v1.3...v1.4

OpenMM-Torch 1.3

This release fixes an issue with CUDA Graphs for the backward pass (#120).

This release can be installed from conda-forge:

conda install -c conda-forge openmm-torch=1.3

What's Changed

• Add AWS GPU Runner by @mikemhenry in #107
• Fix CUDA Graphs for the backward pass by @RaulPPelaez in #120

New Contributors

• @mikemhenry made their first contribution in #107

Full Changelog: v1.2...v1.3

OpenMM-Torch 1.2

This release fixes (#116) the issue of failing minimization with NNP due to a device change (openmm/NNPOps#112).

This release can be installed from conda-forge:

conda install -c conda-forge openmm-torch=1.2

What's Changed

• Document the constructor that takes a scripted module by @RaulPPelaez in #104
• Clone the module on TorchForceImpl initialization by @RaulPPelaez in #116

Full Changelog: v1.1...v1.2

OpenMM-Torch 1.1

This release brings support for PyTorch 2 (#106) and CUDA Graphs (#103).

This release can be installed from conda-forge:

conda install -c conda-forge openmm-torch=1.1

What's Changed

• Attempt at fixing SWIG issues by @peastman in #96
• Add a constructor to TorchForce that takes a torch::jit::Module by @RaulPPelaez in #97
• Use Ubuntu-22 instead of deprecated Ubuntu 18 in CI by @RaulPPelaez in #105
• Making TorchForce CUDA-graph aware by @RaulPPelaez in #103
• Torch2 compatibility by @RaulPPelaez in #106

New Contributors

• @RaulPPelaez made their first contribution in #97

Full Changelog: v1.0...v1.1

OpenMM-Torch 1.0

This release (1.0) marks that OpenMM-Torch has matured to be used for production. We aim to maintain a stable and backward-compatible API for the 1.x releases.

This release can be installed from conda-forge:

conda install -c conda-forge openmm-torch=1.0

What's Changed

• Use Mamba for CI by @raimis in #81
• Update CI for PyTorch 1.12 by @raimis in #83
• Pin swig to <4.1 by @raimis in #86

Full Changelog: v0.8...v1.0

OpenMM-Torch 0.8

This release fixes a bug (#80) which prevented TorchForce from being used within OpenMM.CustomCVForce.

This release can be installed from conda-forge:

conda install -c conda-forge openmm-torch

What's Changed

• Fix the tutorial by @raimis in #77
• Push primary context before invoking PyTorch by @peastman in #78
• Revert "Push primary context before invoking PyTorch" by @raimis in #79
• Fix interoperability with CustomCVForce by @raimis in #80

Full Changelog: v0.7...v0.8

OpenMM-Torch 0.7

This release fixes two packaging issues. No new features have been implemented.

This version can be installed from conda-forge via

conda install -c conda-forge openmm-torch

What's Changed

• Add PyTorch lib directory to library path by @peastman in #72
• Update the test models and CI dependencies by @raimis in #73

Full Changelog: v0.6...v0.7

OpenMM-Torch 0.6

This release fixes an issue where the PyTorch module was always loaded to the GPU device 0, regardless which device OpenMM was set to use (#70). Also, the Python API has been fixed by including TorchForce.getOutputsForces and TorchForce.setOutputsForces (#60).

A new tutorial illustrating Openmm-Torch with the accelerated kernel library NNPOps is available:

This version can be installed from conda-forge via

conda install -c conda-forge openmm-torch

What's Changed

• Fix the Python wrapper of "setOutputsForces" and "getOutputsForces" by @raimis in #60
• Move the PyTorch module to a correct device by @raimis in #70
• The first tutorial of OpenMM-Torch with NNPOps by @raimis in #62

Full Changelog: v0.5...v0.6

OpenMM-Torch 0.5

This release adds the ability to output the computed atomic force directly (#52) without using the back-propagation of energy; and fixes a long-standing issue the CUDA context synchronization (#47, #49), which was causing crashes or incorrect results. All the users are advised to update.

What's Changed

• Improved coordination of CUDA contexts with PyTorch by @peastman in #47
• Update CI by @raimis in #53
• Test if a PyTorch module receives corrects arguments by @raimis in #50
• Models can directly output forces by @peastman in #52
• Fix the synchronisation between the CUDA contexts by @raimis in #49

Full Changelog: v0.4...v0.5

OpenMM-Torch 0.4

This release fixes an error that could cause incorrect force accumulation on the Reference platform.

What's Changed

• Fix the force accumulation in the reference platform by @raimis in #46

Full Changelog: v.03...v0.4