Skip to content

CHANGELOG.md

Latest commit

 

History

History
209 lines (173 loc) · 8.32 KB

CHANGELOG.md

File metadata and controls

209 lines (173 loc) · 8.32 KB

Changelog

All notable changes to this project will be documented in this file.

[0.12.2.dev]

Added

  • Support OpenEquivariance
  • Per-atom stress (atomic virial) support in LAMMPS pair_e3gnn and ASE calculator
  • compute_atomic_virial option in SevenNetCalculator

Changed

  • [Breaking] Rename optional dependency group mliap into mliap12 (reflecting its CUDA 12.x dependency).
  • Add cueq13 and mliap13 optional dependency groups for CUDA 13.x.
  • [Breaking] torchscript file_type is no longer supported in SevenNetCalculator.
  • LAMMPS pair_e3gnn refactored to use pair-wise force (dE/dr) instead of position-based gradient.
  • Deploy no longer replaces force_output with ForceStressOutput; force/stress computed in LAMMPS C++ side.

[0.12.1]

Fixed

  • FlashTP with LAMMPS parallel in torch
  • Single-atom inference failure with ASE+flashTP, LAMMPS-Torch and LAMMPS ML-IAP
  • CI/CD bugs
  • inconsistent argument namings of flashTP

Changed

  • ninja dependency added for FlashTP compile
  • all CLI argument name of enabling flashTP is now 'enable_flash', not 'enable_flashTP'

Added

  • TorchSim interface and docs

[0.12.0]

Added

  • Documentation moved to RTD
  • LAMMPS-MLIAP integration with GhostExchangeOp

Added

Changed

  • ninja dependency added

Fixed

  • Multi modal model finetuning: Pass modal_map into config during multi-fidelity continual training #232
  • omat deploy parallel fixed

[0.11.2]

Changed

  • change cueq default config
  • assign cell volume 0 instead of eps for non-pbc system
  • remove redundant CELL and CELL_SHIFT

Fixed

  • Circular import in error_recorder

[0.11.1]

From here, the version of 'main' branch has 'devX' after it diverges from the latest stable version

CLI interface changed in backward-compatible manner. Now sevenn has subcommands for inference, train, etc

Added

  • subcommand with some aliases
  • strict e3nn version requirement from init.py

Changed

  • pre-commit uses python3.11
  • cuequivaraiance optional libraries
  • some gitignores

Fixed

  • Circular import in sevenn.checkpoint (dev0)
  • Fix typing issues
  • Added missing typings (especially return type)

[0.11.0]

Multi-fidelity learning implemented & New pretrained-models

Added

  • Build multi-fidelity model, SevenNet-MF, based on given modality in the yaml
  • Modality support for sevenn_inference, sevenn_get_modal, and SevenNetCalculator
  • 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
  • Downloading large checkpoints from url (7net-MF-ompa, 7net-omat)
  • D3 wB97M param

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
  • old v1 presets are removed, liquid electrolyte fine-tune yaml is added

Fixed

  • More refactor for shift scale things + few bug fixes
  • Correctly shuffle training set when distributed training is enabled
  • D3 calculator system swap memory error fixed
  • D3 compile uses $HOME/.cache if package directory is not writable

[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

[0.10.3]

Added

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

Changed

  • Now --help do not load unnecessary imports (fast!)
  • README

[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 dependency
  • data_divide_ration defaults to 0.0 (not used)

Fixed

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

[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

[0.10.0]

SevenNet now have CI workflows using pytest and its coverage is 78%! Substantial changes in cli apps and some outputs.

Added

  • [train_v2]: train_v2, with lots of refactoring + support load_testset_path. Original routine is accessible: sevenn -m train_v1.
  • [train_v2]: SevenNetGraphDataset replaces old AtomGrpahDataset, which extends InMemoryDataset of PyG.
  • [train_v2]: sevenn_graph_build for SevenNetGraphDataset. Previous .sevenn_data is accessible with --legacy option
  • [train_v2]: Any number of additional datasets will be evaluated and recorded if it is given as 'load_{NAME}set_path' key (input.yaml).
  • 'Univ' keyword for 'chemical_species'
  • energy_key, force_key, stress_key options for sevenn_graph_build, @thangckt
  • OpenMPI distributed training @thangckt

Changed

  • Read EFS of atoms from y_* keys of .info or .arrays dict, instead of caclculator results
  • Now type_map and requires_grad is hidden inside AtomGraphSequential, and don't need to care about it.
  • 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.

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.

[0.9.5]

Note

This version is not stable, but I tag it as v0.9.5 before making further changes. LAMMPS pair_e3gnn_parallel.* should be re-compiled for the below changes regarding LAMMPS parallel. This is the first changelog and may not reflect all the changes.

Added

  • Stress compute for LAMMPS sevennet parallel
  • sevenn_inference now takes .extxyz input
  • sevenn_inference gives MAE error
  • Experimental sevenn_inference on the fly graph build option

Changed

  • [Breaking] Parallel LAMMPS model changed, old deployed parallel models will not work
  • [Breaking] Parallel LAMMPS takes the directory of potentials as input. Accordingly, sevenn_get_model -p creates a folder with potentials.
  • [Breaking] Except for serial LAMMPS models, force and stress are computed from gradients of edge vectors, not positions.
  • Separate interaction block from model build
  • Add typing for most of functions
  • Remove clang pre-commit hook as it breaks lammps pair files
  • torch.load with weights_only=False
  • Line length limit 80 -> 85
  • Refactor

Fixed

  • Correct batch size for SevenNet-0(11July2024)

[0.9.4] - 2024-08-26

Added

  • D3 correction (contributed from dambi3613) for LAMMPS serial