GitLab

* Improve new dataset API

* Improve more on new dataset API

* fix

* fix reentrance

* Allow all intermediate state of transformation to be reentered

* Add length inference

* fix

* split by ratio

* add dataloader example

* add test for data loader

* Remove everything about chunking

* aev.py

* neurochem trainer

* training-benchmark-nsys-profile.py

* fix eval

* training-benchmark.py

* nnp_training.py

* flake8

* nnp_training_force.py

* fix dtype of species

* fix

* flake8

* requires_grad_

* git ignore

* fix

* original

* fix

* fix

* fix

* fix

* save

* save

* save

* save

* save

* save

* save

* save

* save

* collate

* fix

* save

* fix

* save

* save

* fix

* save

* fix

* fix

* no len

* float

* save

* save

* save

* save

* save

* save

* save

* save

* save

* fix

* save

* save

* save

* save

* fix

* fix

* fix

* fix mypy

* don't remove outliers

* save

* save

* save

* fix

* flake8

* save

* fix

* flake8

* docs

* more docs

* fix test_data

* remove test_data_new

* fix

* massive training time improvement

* flake8

* improve validation also

* improve training-benchmark.py

* fix devices

* send num_atoms to GPU

* rerun

* Add warning to ChemicalSymbolsToInts

* Change ocurrences of ChemicalSymbolsToInts in the code to reflect safe usage

* flake8

* Add warning to call also

* Add clarification

* docs dont fetch magic functions so documentation is moved to the class docstring

* fix clarification

* flake8

* bypass slow code

* delete reference to all_atoms which was unused

* delete whitespace

* make flake8 happy

* rerun

* actual change was off

* typo did not turn on bypassing code

* Add CODATA and IUPAC unit conversion factors

* Add units to main module

* change neurochem and training-benchmark to use the new hartree2kcalmol conversion

* change training-benchmark to use hartree2kcalmol conversion

* change comp6 to use the new hartree2kcalmol conversion

* change training-benchmark without nsys to also use hartree2kcalmol conversion

* change examples to use hartree2kcalmol conversion

* Rename ase to ase_ani to avoid naming conflicts that come from naming internal module the same as an external one we are using

* fix import

* Add ASE's hartree_to_ev conversion to compare with codata 2018

* Standarize our units to be essentially the same as ASE and CODATA 2014

* Change vibration_analysis to use the consistent constants

* Fix explanation in docstring

* Add millieV conversion factor

* Add millieV conversion factor to vibrational analysis

* Add clarification

* flake8

* revert name change

* Fix typo in function name

* Add units to __all__'

* Improve units docstring and comments in preparation for docs

* delete pad from docs

* Add units to api.rst

* minor formatting of docstrings and comments

* Add functions into the API

* final formatting changes

* flake8

* try to make mypy happy

* Checking if mypy prefers this

* rerun

* Use namedtuple to improve API

* improve

* Remove ignite

* remove neurochem-test

* remove cache-aev

* Move unittest check to GitHub Actions

Tests are parallelized

* Delete tests.yml

* Update setup.py

* Create test_requirements.txt

* Update unittest.yml

* Update unittest.yml

* Update README.md

* Delete install_dependencies.sh

* Delete install_dependencies_python2.sh

* Update unittest.yml

* split

* split

* fix

* fix

* -v

* more

* more

* fix

* fix

* flake8

* transform

* reduce testBenzeneMD

* version

* reduce number of epoches

* further reduce time

* Update docs.yml

* outlier removal process fixed

* remove outlier energies if exist

* Update nnp_training to have identical setup to NC

* fix

* add LR decay scheduler for both optimizers

* fix

* Port to torch.bool data type where it should be

* more

* more

* fix snoop

* hopefully fixed

* fix ignite

* remove snoop

* flake8

* using least-squares to compute atomic self energies from the dataset

* self atomic energy calculation in the example training file

Add AdamW optimizer, Add docs of nnp training to train a real ANI-1x model, remove h5py and ignite from dependencies, rename MAEMetric -> MaxAEMetric, use torch.utils.tensorboard to replace tensorboardX (#224)

* add ANI model zoo

* Update cache_aev.py