refactor: uncouple Descriptor and Fitting from Trainer #2549
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Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Codecov ReportPatch coverage:
Additional details and impacted files@@ Coverage Diff @@
## devel #2549 +/- ##
==========================================
- Coverage 75.35% 72.93% -2.42%
==========================================
Files 227 234 +7
Lines 23816 25947 +2131
Branches 1666 1852 +186
==========================================
+ Hits 17947 18925 +978
- Misses 4793 5845 +1052
- Partials 1076 1177 +101
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Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
iProzd
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Jun 1, 2023
iProzd
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Jun 1, 2023
Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
wanghan-iapcm
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Jun 12, 2023
Fix a bug introduced in #2549. Add tests for it. --------- Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>
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Jul 20, 2023
Add an experimental model called pairwise DPRc, which is fragment-based and integrated with QM/MM. Compression inference and training are supported. Unit tests and documentation have been added. Some features or bugfix to implement this PR have been merged in #2549, #2600, #2601, #2604, #2631, #2635, #2665, #2666, #2667, and #2679. This PR makes some changes to `model.build_descrpt` additionally: - fix errors when the suffix is not empty - fix errors when `fparam` or `aparam` are given - support model-customized `input_map` --------- Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
github-merge-queue bot
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Oct 23, 2024
It was forgotten in #2549 <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Introduced the DPA-1 model with an attention mechanism for molecular simulation. - Added the `se_a_mask` descriptor for DP/MM simulations with dynamic atom counts. - Expanded support for multi-task fine-tuning in PyTorch. - **Documentation Enhancements** - Improved clarity and detail in various documents, including model compression, DPLR model training, and fine-tuning processes. - Updated references to follow a standardized format, enhancing navigation and understanding. - **Bug Fixes** - Corrected references and parameters across multiple documents to ensure accuracy in model configurations and training instructions. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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