Closed aleaverfay closed 7 months ago
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Files | Patch % | Lines |
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tmol/tests/support/test_database_converters.py | 0.00% | 12 Missing :warning: |
tmol/utility/reactive.py | 57.14% | 6 Missing :warning: |
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I think this is ready to merge
This enables tmol to work with the latest torch (2.2) and python (3.12). It also (hopefully) simplifies the packaging of tmol so that it can be used more easily in a greater number of environments.
To support newer pytorch versions the compiler std version is bumped to c++17. There are also some additions of explicit device placements for tensors because torch has gotten more strict about automatically moving tensors in indexing operations. The deprecated torch.testing.assert_allclose is replaced by torch.testing.assert_close (see RFC: retire torch.testing.assert_allclose in favor of torch.testing.assert_close pytorch/pytorch#61844) To support python >= 3.11 typish is removed as a dependency and replaced by a vendored version which fixes a bug in equality comparison of subscripted types. package configuration is moved into pyproject.toml and now includes specification of dependencies so that they are automatically fetched on install. This also enables installing directly from the git repo ( pip install git+https://github.com/kleinhenz/tmol.git@bump_versions) git version information is embedded into the library and available at tmol.version using setuptools_scm. The Dockerfile is simplified by using micromamba base images in the env.yml the cudatoolkit is changed to the version provided by nvidia at nvidia/label/cuda-12.1.1::cuda. All other dependencies are moved to pip since it makes propagating dependencies to other projects easier. A frozen set of known good dependency versions and a script to update them are provided in environments/linux-cuda.
The new order of operations for installing the conda/mamba environment for development is:
Authored by Joseph Kleinhenz kleinhej@gene.com