Releases: ICAMS/grace-tensorpotential
Release 0.5.7
Bug fix for the presets config
Full Changelog: 0.5.6...0.5.7
Release 0.5.6
What's Changed
-
update GRACE-1L/2L presets according to latest foundational models (with suffix _latest)
-
update input file template with new recommended optimizer settings
- version 0.5.6 by @yury-lysogorskiy in #21
Full Changelog: 0.5.5...0.5.6
0.5.5
- bugfix reduce_elements functionality when elements are not ordered lexicographically
- add _configure_keras_backend to the top-most module
What's Changed
- Release 0.5.5 by @yury-lysogorskiy in #19
Full Changelog: 0.5.4...0.5.5
0.5.4
Windows/MacOS support
What's Changed
- Feature/windows by @yury-lysogorskiy in #16
Full Changelog: 0.5.3...0.5.4
0.5.3
0.5.2
Update to 0.5.2:
add more foundational UMLIPS (GRACE-1L/2L-OMAT/OAM-medium/large): checkpoints and saved models
add grace_utils::resave_checkpoint
grace_predict: add stress prediction
grace_preprocess: add EQUI_NEIGH_STRATEGY, add FULL_ELEMENTS preset, add --remove_stage1 arg, add support of cutoff dict
upd documentation
asecalculator.py::TPCalculator: change defaults for padding pad_neighbors_fraction: 0.25 -> 0.05, pad_atoms_number=10->1
gracemaker.py:
-- add dataset plotting
-- add more learning rate schedulers, store epoch into checkpoint
instructions: add MLPRadialFunction_v2, InvariantLayerRMSNorm and TrainableShiftTarget
What's Changed
- Release/0.5.2 by @yury-lysogorskiy in #11
Full Changelog: 0.5.1...0.5.2
0.5.1
Update to 0.5.1: Fine-tuning of foundation models
- gracemaker: add functionality for finetuning of foundation models
- add GRACE-*-OMAT foundation models and checkpoints for finetuning
- add grace_utils for model conversion, exporting and summary
- README.md: add important notes for model conversion
- implementation details: using dict-of-instructions instead of list-of-instructions
0.4.5
Update to 0.4.5:
- add df2extxyz, grace_predict and grace_preprocess
- update gracemaker (including bugfix for finetuning)
- implement distributed fit and grace_preprocess
- add layer normalization to GRACE models
- optimized padding strategy for TPCalculator
- add pyproject.toml
- add two OAM foundation models
0.4.4
add foundation model: MP_GRACE_2L_r6_11Nov2024
0.4.3
bugfix: max_structs is np.array in padding
What's Changed
- max_structs is np.array in padding
- add models.png into doc by @yury-lysogorskiy in #3
- upd docs/requirements.txt (add mkdocs-glightbox) by @yury-lysogorskiy in #4
Full Changelog: 0.4.2...0.4.3