v0.11.0

The official release of v0.11.0 includes a multi-fidelity learning feature and new pre-trained models (7net-MF-ompa, 7net-omat)

CHANGELOG.md

What's Changed

• fix: d3 calc ._lib init by @YutackPark in #168
• Multimodal + cuEq + ... by @Jaesun0912 in #71
• docs: remove MF from main + update citation info by @YutackPark in #169
• Feats: add DFT-D3(BJ) parameters for omegaB97M & calc error fix & D3 compile to cache + Docs: application ref paper by @SuyeonJu in #173
• Bug fixes + chore by @YutackPark in #181
• refactor: sevenn.sevenn_logger => sevenn.logger with deprecation warn by @YutackPark in #182
• fix: lower python version compatible typing by @YutackPark in #183
• Add: 7net-mf-ompa, 7net-omat by @hexagonrose @Jaesun0912 @YutackPark in #184

New Contributors

• @Jaesun0912 made their first contribution in #71
• @SuyeonJu made their first contribution in #173

Full Changelog: v0.10.4...v0.11.0

v0.11.0-checkpoint

Release for model checkpoints. Official v0.11.0 will be released soon.

1. SevenNet-MF-ompa
2. SevenNet-omat

v0.11.0-alpha

Pre-release of multi modal feature.

[0.11.0]

Added

• Build multi-fidelity model, SevenNet-MF, based on given modality in the yaml
• Modality support for sevenn_inference, sevenn_get_modal, and SevenNetCalculator
• [cli] sevenn_cp tool for checkpoint summary, input generation, multi-modal routines
• Modality append / assign using sevenn_cp
• Loss weighting for energy, force and stress for corresponding data label
• Ignore unlabelled data when calculating loss. (e.g. stress data for non-pbc structure)
• Dict style dataset input for multi-modal and data-weight
• (experimental) cuEquivariance support

Added (code)

• sevenn.train.modal_dataset SevenNetMultiModalDataset
• sevenn.scripts.backward_compatibility.py
• sevenn.checkpoint.py

Changed

• Sort instructions of tensor product in convolution (+ fix flipped w3j coeff of old model)
• Lazy initialization for IrrepsLinear and SelfConnection*
• Checkpoint things using sevenn/checkpoint.py
• e3nn >= 0.5.0, to ensure changed CG coeff later on
• pandas as dependency

Fixed

• More refactor for shift scale things + few bug fixes
• Correctly shuffle training set when distributed training is enabled

What's Changed

• sync main by @YutackPark in #147
• fix: d3 calc ._lib init by @YutackPark in #168
• Multimodal + cuEq + ... by @Jaesun0912 in #71
• docs: remove MF from main + update citation info by @YutackPark in #169

New Contributors

• @Jaesun0912 made their first contribution in #71

Full Changelog: v0.10.4...v0.11.0-alpha

v0.10.4

Important: last version that allows e3nn < 0.5.0

[0.10.4]

Added

• feats: D3 calculator

Fixed

• bug: info dict sharing (therefore energy stress) when structure_list used
• torch >= 2.5.0 works
• numpy >= 2.0 works (need more testing)

Changed

• sevennet_calculator.py => calculator
• fine tunine preset to use original loss function (Huber) and loss weights

What's Changed

• Update README.md by @hexagonrose in #149
• fix: bugfix info dict sharing of structure_list by @YutackPark in #157
• [pre-commit.ci] pre-commit autoupdate by @pre-commit-ci in #156
• CUDA-accelerated ASE D3 calculator by @dambi3613 in #152
• maintenence: torch >= 2.5.0, numpy >= 2.0.0 by @YutackPark in #164
• docs: remove torch version cap by @YutackPark in #165

Full Changelog: v0.10.3...v0.10.4

v0.10.3

[0.10.3]

Matbench
Our new model SevenNet-l3i5 is now available.

Added

• SevenNet-l3i5, checkpoint, preset. (keywords: 7net-l3i5, sevennet-l3i5)

Changed

• Fast --help (do not import torch)
• README refined

What's Changed

• Add: sevennet-l3i5 by @YutackPark in #136
• Upload l3i5 & update README.md by @JisuJung928 in #137
• Fast --help by @YutackPark in #139
• Sevennet-l3i5 unit test by @YutackPark in #141
• Fix: add l3i5 cp as data by @YutackPark in #142

New Contributors

• @JisuJung928 made their first contribution in #137

Full Changelog: v0.10.2...v0.10.3

v0.10.2

[0.10.2]

Added

• Accelerated graph build routine if matscipy is installed @hexagonerose
• matscipy vs. ase neighborlist unit test
• If valid set is not given but data_divide_ratio is given, validaset is created using random split. (shift, scale, and conv_denoiminator uses original whole statistics)

Changed

• matscipy is included as a dependency
• data_divide_ration defaults to 0.0 (meaning not used)

Fixed

• For torch version >= 2.4.0, Loading graph dataset no more raises warnings.
• Raise error when unknown element is found (SevenNetCalculator)

What's Changed

• [Feat] change ase.neighborlist to from matscipy.neighbours by @hexagonrose in #124
• [refactor] make _remove_self_edges be skipped when doing matscipy graph build by @hexagonrose in #129
• docs: update sevenn_graph_build of README.md by @YutackPark in #128
• [Feat] add graph build test of ase and matscipy in pytest by @hexagonrose in #131
• Add: data split by @YutackPark in #134

New Contributors

• @hexagonrose made their first contribution in #124

Full Changelog: v0.10.1...v0.10.2

v0.10.1

[0.10.1]

Added

• experimental SevenNetAtomsDataset which is memory efficient, can be enabled with dataset_type='atoms'
• Save meta data & statistics when the SevenNetGraphDataset saves its data.

Changed

• Save checkpoint_0.pth (model before any training)
• SevenNetGraphDataset._file_to_graph_list -> SevenNetGraphDataset.file_to_graph_list
• Refactoring SevenNetGraphDataset, skips computing statistics if it is loaded, more detailed logging
• Prefer use .get when accessing config dict

Fixed

• Fix error when loading SevenNetGraphDataset with other types of data (ex: extxyz) in one dataset

Full Changelog: v0.10.0...v0.10.1

What's Changed

• chore: update dependencies (PyG >= 2.5.0) by @YutackPark in #110
• v0.10.1 by @YutackPark in #112
• docs: update torch version by @YutackPark in #116
• refactor: file not found error + warnings for graph dataset by @YutackPark in #119
• merge main by @YutackPark in #122
• refactor: please use get by @YutackPark in #121

v0.10.0

[0.10.0]

SevenNet now has CI workflows and its python coverage is 78%!
Substantial changes in command-line apps and their outputs.
Previous functionalities are still accessible with correct flags (sevenn -m train_v1 ... , sevennet_graph_build --legacy ...)

Added

• sevenn_preset for below changes
• [train_v2]: train_v2, with lots of refactoring, support load_testset_path.
• [train_v2]: SevenNetGraphDataset replaces old AtomGrpahDataset, which extends InMemoryDataset of PyG.
• [train_v2]: sevenn_graph_build for SevenNetGraphDataset.
• [train_v2]: Any additional datasets will be evaluated and recorded if it is given as 'load_{NAME}set_path' key.
• Univ keyword for chemical_species
• More options: energy_key, force_key, stress_key for sevenn_graph_build, than ase.calculator @thangckt
• OpenMPI distributed training @thangckt

Changed

• Some cumbersome things(type_map, requires_grad ), that hurt readability, are now hidden inside AtomGraphSequential.
• log.sevenn and lc.csv automatically find a safe filename (log0.sevenn, log1.sevenn, ...) to avoid overwriting.
• [train_v2]: train_v2 loads its training set via load_trainset_path, rather than previous load_dataset_path.
• [train_v2]: log.csv -> lc.csv, and columns have no units, (easier to postprocess with it) but still on log.sevenn.
• [train_v2]: Train valid split by ratio is temporarily removed
• Previous presets are renamed with _v1 suffix

Fixed

• [e3gnn_serial]: can continue simulation even when atom tag becomes not consecutive (removing atom dynamically), @gasplant64
• [e3gnn_parallel]: undefined behavior when there is no atoms to send/recv (for non pbc system)
• [e3gnn_parallel]: incorrect force/stress in some edge cases (too small simulation cell & 2 process)
• [e3gnn_parallel]: revert commit 14851ef, now e3gnn_parallel is sane.
• [e3gnn_*]: += instead of = when saving virial stress and forces @gasplant64
• Now Logger correctly closes a file.
• ... and lots of small bugs I found during writing pytest.

New Contributors

• @thangckt made their first contribution in #89
• @gasplant64 made their first contribution in #81
• @pre-commit-ci made their first contribution in #101

v0.9.3

Warning: This release has a serious bug in LAMMPS parallel. Please use v0.9.3.post1 in the 'tags', or use pip install.

SevenNet is released to PyPI, project is managed using pyproject.toml, not setup.py

• PyPI release + docs
• torch_scatter dependency removed
• torch_geometric dependency added to the pyproject.toml

Features:

• sevenn_preset for basic training yaml files
• sevenn_patch_lammps for easier installation
• keyword input for pre-trained models: continue, sevenn_get_model, sevennet_calculator

Bugfix:

• C++17 for torch version > 2.0

Known bug:

• In training yaml, scale: 'elemwise_force_rms' is broken. Fixed in github, but not in pip.

The last snapshot of XPLOR cutoff bug

The last snapshot of SevenNet has XPLOR cutoff bug and wrong SevenNet-0 potential.