GitLab

* 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

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* collate

* fix

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* fix

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* fix

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* fix

* no len

* float

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* fix

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* 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

* Add tuple of atomic masses

* Add get_atomic_masses function, to get masses from periodic table indices (znumbers)

* Fix bug that prevented using ASE together with periodic_table_index

* ASE has to know if the model has PTI or not

* Allow for models that don't have a periodic_table_index attribute

* now vibrational analysis can be computed without explicit masses if periodic_table_index=True

* Add atomic masses calculator to docs

* flake8

* flake8

* flake8
Co-authored-by: Gao, Xiang <qasdfgtyuiop@gmail.com>

* Remove deprecated API and add a docstring to PaddedBatchChunkDataset

* Remove reference to deprecated API

* Added PaddedBatchChunkDataset to docs

* remove unused warnings

* 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

* Improvements on docs

* Add tips

* Remove AEV cacher

* more

* more

* more

* flake8

* further cleanup

* Remove ignite

* remove neurochem-test

* remove cache-aev

* split

* clean

* docs

* docs

* Update new.py

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