v2.1.1

What's Changed

• fixes a bug: due to new python versions, the hydra config_dir was not found

Full Changelog: v2.1.0...v2.1.1

v2.1.0

What's Changed

• Update README.md by @jnsLs in #574
• windows issue with index tensors by @jnsLs in #579
• all tutorials on cpu by @jnsLs in #580
• fix ISO17 database by @stefaanhessmann in #582
• doc: Readme: various minor fixes by @Maltimore in #586
• fix typo: propery -> property by @Maltimore in #584
• requirements: add pytest-benchmark by @Maltimore in #585
• requirements.txt is linked to setup.py by @jnsLs in #588
• [WIP] README: remove outdated or less important information by @Maltimore in #595
• torch.testing: update deprecated assert_allclose by @Maltimore in #594
• hydra: add self to defaults list to avoid warning by @Maltimore in #593
• doc: put link to docs earlier in the readme, and add tests README by @Maltimore in #597
• provide batch size to self.log() of lightning module to prevent warning by @Maltimore in #598
• replace setup.py with pyproject.toml by @Maltimore in #596
• Unpin dependencies and cleanup by @Maltimore in #599
• Ignore model hyperparameters when saving because they are saved at checkpointing by @Maltimore in #600
• random split is default by @jnsLs in #606
• Implemented a stratified sampler by @jnsLs in #539
• added wandb logger by @jnsLs in #610
• quick model save patch by @jnsLs in #614
• Adding the functionality to define matmul precision for pytorch in configs by @khaledkah in #611
• Embedding spin multiplicity and charge based on SpookyNet implementation by @epens94 in #608
• fix backwards compatibility and clean up by @stefaanhessmann in #617
• fixed device (cpu) in qm9 tutorial by @jnsLs in #621
• Add tmqm dataset by @sgugler in #623
• Kk/qm7 x by @khaledkah in #616
• batchwise optimizer is deprecated by @jnsLs in #638
• test rtd by @jnsLs in #640
• if no seed is specified, it is chosen randomly by @jnsLs in #636
• Update spkdeploy by @jnsLs in #644
• restructure embeddings to avoid issues with torch jit by @stefaanhessmann in #634
• Jl/upgrade black by @jnsLs in #645
• added black workflow by @stefaanhessmann in #648
• Delete src/scripts/test_ase.py by @stefaanhessmann in #652
• md seed is initialized randomly if not specified by @jnsLs in #651
• drafting the load_model method with conversion between spk versions by @jnsLs in #646
• upgrade dependencies to numpy 2 by @stefaanhessmann in #654
• load model and upgrade version in spkpredict by @jnsLs in #655
• fixes bug in RemoveOffsets for intensive properties by @stefaanhessmann in #656
• update versions for release by @stefaanhessmann in #659
• fixes bug and updates to new simpy verison by @stefaanhessmann in #658

New Contributors

• @Maltimore made their first contribution in #586
• @khaledkah made their first contribution in #611
• @sgugler made their first contribution in #623

Full Changelog: v2.0.4...v2.1.0

v2.0.4

Updated documentation and requirements, minor bug fixes.

What's Changed

• Update citations of software papers by @NiklasGebauer in #528
• fixed md22 downloading method by @jnsLs in #530
• Jl/fix md22 by @jnsLs in #532
• Sh/batchwise optimizer by @Stefaanhess in #531
• raise Exception if array is passed for energy in calculator + typehint by @Stefaanhess in #533
• device can be specified when deploying models by @jnsLs in #544
• fix atomic mass for aspirine lammps example by @Stefaanhess in #545
• old field schnet data can be converted to new input dimension by @jnsLs in #550
• fixed calculator stress bug by @jnsLs in #552
• fixed training parameters by @jnsLs in #557
• url for uracil data has changed by @jnsLs in #558
• fixed device bug in tutorial 03 - clean by @jnsLs in #559
• updated pytorch-lightning requirement by @jnsLs in #560
• updated tutorial 1 by @Stefaanhess in #562
• data dimensions are updated in materials tutorial by @jnsLs in #564
• Update requirements.txt by @jnsLs in #566
• Update setup.py by @Stefaanhess in #572
• Update setup.py by @Stefaanhess in #573

Full Changelog: v2.0.3...v2.0.4

v2.0.3

What's Changed

• bug fix: per_atom_output_key in Atomwise by @Stefaanhess in #527

Full Changelog: v2.0.2...v2.0.3

v2.0.2

Updated pytorch-lightning, updated Lammps interface, enhanced batchwise optimization, general small bug fixes.

What's Changed

• improved batchwise optimization by @jnsLs in #508
• num_val_workers and num_test_workers can now be set to 0 by @NiklasGebauer in #515
• adapted to new pytorch-lightning version by @jnsLs in #517
• fix per_atom_output_key usage in Atomwise by @Vosatorp in #523
• data.load_properties can now be set to an empty list by @NiklasGebauer in #524
• allow to also use higher lammps versions by @Stefaanhess in #522
• updated batchwise calculator by @jnsLs in #525

New Contributors

• @Vosatorp made their first contribution in #523

Full Changelog: v2.0.1...v2.0.2

v2.0.1

Updated SchNetPack 2.0 release, which fixes a series of bugs and adds an interface to LAMMPS.

What's Changed

• Added materials tutorial to docs index by @mgastegger in #479
• fix bug in OMDB dataset by @Stefaanhess in #481
• Updated MD17 download urls by @mgastegger in #483
• Update default_run.yaml by @NiklasGebauer in #486
• Update README.md by @Stefaanhess in #489
• fix: LightningLoggerBase was removed in lightning 1.9 by @Stefaanhess in #491
• fix: add support for force models in spkpredict by @Stefaanhess in #492
• Sh/spkpredict by @Stefaanhess in #493
• fixed dtype of materiels project dataset by @Stefaanhess in #498
• check for legacy API-key in materials project by @Stefaanhess in #499
• reviewed the lammps doc files by @jnsLs in #500
• Sh jl/lammps by @Stefaanhess in #501
• Niklas gebauer docstring fixes by @NiklasGebauer in #502
• Fix bugs in MD module by @mgastegger in #503
• Removed deprecated arguments … by @NiklasGebauer in #504
• added schnetpack-gschnet extension to readme… by @NiklasGebauer in #505
• Updated README and fixed deprecated numpy dtype by @mgastegger in #506

Full Changelog: v2.0.0...v2.0.1

v2.0.0

Notes

This is the first release of SchNetPack 2.0 which uses the Hydra configuration framework, Pytorch Lightning and a new indexing scheme.
It also includes an improved data pipeline, modules for equivariant neural networks and a PyTorch implementation of molecular dynamics.

What's Changed

• Inital commit for v1 rewrite by @ktschuett in #267
• center transformations by @Stefaanhess in #271
• Mg/torch env by @mgastegger in #274
• Kts/qm9datamodule by @ktschuett in #275
• Training script driven by Hydra+Lightning by @ktschuett in #277
• Implement training of potential energy surfaces by @ktschuett in #278
• Add split file by @ktschuett in #282
• PaiNN representation by @ktschuett in #284
• Postprocessors and TorchScript by @ktschuett in #285
• Mg/symfuncs by @mgastegger in #287
• Initial API docs by @ktschuett in #293
• Fix problem with transforms in new lightning version by @ktschuett in #294
• stress and custom experiment by @Stefaanhess in #292
• Update docs (and fix postprocess bug) by @ktschuett in #295
• Mg/calculators by @mgastegger in #296
• Refactor models by @ktschuett in #297
• fix small bug by @Stefaanhess in #298
• Sh/datasets by @Stefaanhess in #300
• Proposal for MultiPropertyModel by @Stefaanhess in #299
• add epsilon to painn by @Stefaanhess in #301
• Some minor updates by @ktschuett in #305
• Fix API docs by @ktschuett in #306
• Unify model classes & refactor configs by @ktschuett in #309
• Fix ModelOutput package by @ktschuett in #310
• add bessel representation for future painn usage by @Divide-By-0 in #311
• Update examples & add data workdir by @ktschuett in #314
• Dipole moment & polarizability by @ktschuett in #316
• Dynamics caching neighborlist by @ktschuett in #320
• Dev by @jnsLs in #322
• Add long range cutoff by @ktschuett in #325
• Mg/md by @mgastegger in #315
• Refactor configs and add predict script by @ktschuett in #334
• Fix install bug by @ktschuett in #335
• Add automatic position derivatives by @ktschuett in #341
• Update QM9 tutorial by @ktschuett in #347
• ZBL Potential, Electrostatics (+Ewald summation) and stress tensor fixes by @mgastegger in #349
• Fixes to some MD desfaults and torchscript issues by @mgastegger in #350
• Disable automatic use of torchscript in MD calculators by @mgastegger in #351
• Response properties and field representations by @mgastegger in #339
• Fixed derivative graph settings for basic response properties by @mgastegger in #352
• Fixed sign for shift type cutoff by @mgastegger in #353
• Refactor AtomisticModel by @ktschuett in #354
• Fix bug when using ddp with set run.id by @ktschuett in #359
• Fix mixing bias by @ktschuett in #365
• Fix mixing residual by @ktschuett in #366
• fixed aggregation_mode bug for avg pooling by @jnsLs in #361
• Sh/ep device by @Stefaanhess in #360
• Fix AtomsDataSubset for use inside ConcatAtomsData by @chgaul in #357
• Add learning rate warmup & SGD config by @ktschuett in #370
• Fixed creation of subset in BaseAtomsData by @NiklasGebauer in #369
• Fix DDP training by @ktschuett in #372
• Updated for new yaml behavior by @mgastegger in #375
• Nwag/comment-update by @NiklasGebauer in #374
• Fix OMDB _convert dataset preparation by @bartolsthoorn in #373
• Fix pin_memory and some deprecation warnings by @ktschuett in #378
• Update tutorials and filter outputs by @ktschuett in #377
• Add conversion script for old datasets by @ktschuett in #380
• Fixed bug in map_properties by @mgastegger in #381
• Fix testing bc lightning API changed by @ktschuett in #382
• Updated MD docstrings and tutorial by @mgastegger in #383
• Wrapping of atom positions under PBC by @mgastegger in #385
• Fixed energy logging for multiple molecules by @mgastegger in #386
• Some refactoring and cleanup by @ktschuett in #387
• Retrained ethanol model for new postprocessing convention by @mgastegger in #388
• Added on_step_finalize in MD simulation hooks by @mgastegger in #390
• Updated weight init in FieldSchNet representation by @mgastegger in #391
• Added tmpdir functionality for MDs, fixed calculator bug by @mgastegger in #395
• Improved config loading for MD by @mgastegger in #396
• Fixed criterion for recomputing MD neighborlists by @mgastegger in #398
• Fixed using subset in ASEAtomsData.iter_properties by @NiklasGebauer in #393
• update deprecated code to new torch version by @Stefaanhess in #399
• Fix strain input module by @ktschuett in #403
• Add resolver for tmp directory by @NiklasGebauer in #406
• Fix #401 by @ktschuett in #404
• Added tempfile import for custom tmpdir resolver by @mgastegger in #408
• Added routine to NeighborListMD to properly filter out pairs due to the buffer region by @mgastegger in #409
• Removed n_out argument from DipoleMoment and Polarizability layer docstrings by @mgastegger in #411
• Fix PyTorch Lightning deprecations by @ktschuett in #414
• Consider only a selection of atomic forces in training, validation and testing, and ASE neighborlist with skin implemented by @jnsLs in #405
• Added a few classes util for structure relaxations (in particular MOMONANO) by @jnsLs in https://g...

v2.0.0 pre

What's Changed

• Inital commit for v1 rewrite by @ktschuett in #267
• center transformations by @Stefaanhess in #271
• Mg/torch env by @mgastegger in #274
• Kts/qm9datamodule by @ktschuett in #275
• Training script driven by Hydra+Lightning by @ktschuett in #277
• Implement training of potential energy surfaces by @ktschuett in #278
• Add split file by @ktschuett in #282
• PaiNN representation by @ktschuett in #284
• Postprocessors and TorchScript by @ktschuett in #285
• Mg/symfuncs by @mgastegger in #287
• Initial API docs by @ktschuett in #293
• Fix problem with transforms in new lightning version by @ktschuett in #294
• stress and custom experiment by @Stefaanhess in #292
• Update docs (and fix postprocess bug) by @ktschuett in #295
• Mg/calculators by @mgastegger in #296
• Refactor models by @ktschuett in #297
• fix small bug by @Stefaanhess in #298
• Sh/datasets by @Stefaanhess in #300
• Proposal for MultiPropertyModel by @Stefaanhess in #299
• add epsilon to painn by @Stefaanhess in #301
• Some minor updates by @ktschuett in #305
• Fix API docs by @ktschuett in #306
• Unify model classes & refactor configs by @ktschuett in #309
• Fix ModelOutput package by @ktschuett in #310
• add bessel representation for future painn usage by @Divide-By-0 in #311
• Update examples & add data workdir by @ktschuett in #314
• Dipole moment & polarizability by @ktschuett in #316
• Dynamics caching neighborlist by @ktschuett in #320
• Dev by @jnsLs in #322
• Add long range cutoff by @ktschuett in #325
• Mg/md by @mgastegger in #315
• Refactor configs and add predict script by @ktschuett in #334
• Fix install bug by @ktschuett in #335
• Add automatic position derivatives by @ktschuett in #341
• Update QM9 tutorial by @ktschuett in #347
• ZBL Potential, Electrostatics (+Ewald summation) and stress tensor fixes by @mgastegger in #349
• Fixes to some MD desfaults and torchscript issues by @mgastegger in #350
• Disable automatic use of torchscript in MD calculators by @mgastegger in #351
• Response properties and field representations by @mgastegger in #339
• Fixed derivative graph settings for basic response properties by @mgastegger in #352
• Fixed sign for shift type cutoff by @mgastegger in #353
• Refactor AtomisticModel by @ktschuett in #354
• Fix bug when using ddp with set run.id by @ktschuett in #359
• Fix mixing bias by @ktschuett in #365
• Fix mixing residual by @ktschuett in #366
• fixed aggregation_mode bug for avg pooling by @jnsLs in #361
• Sh/ep device by @Stefaanhess in #360
• Fix AtomsDataSubset for use inside ConcatAtomsData by @chgaul in #357
• Add learning rate warmup & SGD config by @ktschuett in #370
• Fixed creation of subset in BaseAtomsData by @NiklasGebauer in #369
• Fix DDP training by @ktschuett in #372
• Updated for new yaml behavior by @mgastegger in #375
• Nwag/comment-update by @NiklasGebauer in #374
• Fix OMDB _convert dataset preparation by @bartolsthoorn in #373
• Fix pin_memory and some deprecation warnings by @ktschuett in #378
• Update tutorials and filter outputs by @ktschuett in #377
• Add conversion script for old datasets by @ktschuett in #380
• Fixed bug in map_properties by @mgastegger in #381
• Fix testing bc lightning API changed by @ktschuett in #382
• Updated MD docstrings and tutorial by @mgastegger in #383
• Wrapping of atom positions under PBC by @mgastegger in #385
• Fixed energy logging for multiple molecules by @mgastegger in #386
• Some refactoring and cleanup by @ktschuett in #387
• Retrained ethanol model for new postprocessing convention by @mgastegger in #388
• Added on_step_finalize in MD simulation hooks by @mgastegger in #390
• Updated weight init in FieldSchNet representation by @mgastegger in #391
• Added tmpdir functionality for MDs, fixed calculator bug by @mgastegger in #395
• Improved config loading for MD by @mgastegger in #396
• Fixed criterion for recomputing MD neighborlists by @mgastegger in #398
• Fixed using subset in ASEAtomsData.iter_properties by @NiklasGebauer in #393
• update deprecated code to new torch version by @Stefaanhess in #399
• Fix strain input module by @ktschuett in #403
• Add resolver for tmp directory by @NiklasGebauer in #406
• Fix #401 by @ktschuett in #404
• Added tempfile import for custom tmpdir resolver by @mgastegger in #408
• Added routine to NeighborListMD to properly filter out pairs due to the buffer region by @mgastegger in #409
• Removed n_out argument from DipoleMoment and Polarizability layer docstrings by @mgastegger in #411
• Fix PyTorch Lightning deprecations by @ktschuett in #414
• Consider only a selection of atomic forces in training, validation and testing, and ASE neighborlist with skin implemented by @jnsLs in #405
• Added a few classes util for structure relaxations (in particular MOMONANO) by @jnsLs in #415
• New datasets and fixes by @ktschuett in #417
• Fixed inverted grad context for calculator by @mgastegger in https://github.com/atomistic-machine-learning/schnetpack/...

v1.0.1

What's Changed

• Sh/ep device by @Stefaanhess in #360
• Fix AtomsDataSubset for use inside ConcatAtomsData by @chgaul in #357
• Updated for new yaml behavior by @mgastegger in #375
• Fix OMDB _convert dataset preparation by @bartolsthoorn in #373
• update deprecated code to new torch version by @Stefaanhess in #399

New Contributors

• @chgaul made their first contribution in #357

Full Changelog: v1.0.0...v1.0.1

v1.0.0

Note

This is the last release before a major update. In the next version, we plan to adopt Hydra and PyTorch Lightning, switch to indexing instead of masking and make the networks compatible with TorchScript. Therefore, there will be breaking changes.

New Contributors

• @heytitle made their first contribution in #12
• @pankessel made their first contribution in #14
• @bartolsthoorn made their first contribution in #26
• @WardLT made their first contribution in #38
• @RoberTnf made their first contribution in #40
• @FarnazH made their first contribution in #76
• @Dom1L made their first contribution in #101
• @lmj1029123 made their first contribution in #117
• @nzhan made their first contribution in #158
• @jan-janssen made their first contribution in #164
• @dumkar made their first contribution in #174
• @giadefa made their first contribution in #205
• @zyt0y made their first contribution in #266

Full Changelog: v0.2.1...v1.0.0