GitLab

* Use PyTorch's TestCase to compare tensor

* save

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* Update test_energies.py

* Update test_ase.py

* save

* flake8

* Remove test gradient from aev tests

* Add a dedicated test gradient for one model, and make it feasible

* add test_grad to unittests

* Add some comments and fix formatting

* flake8

* flake8

* remove unused var

* delete transform function, which was legacy from old pytorch probably

* Delete random_skip function, which was unused

* Allow testNeuroChem to use cuda if available, which makes it much faster

* small modification for consistency

* remove unused import

* simplify device call

* remove unused variable

* add main to test_grad

* Allow easily loading individual models

* Hopefully make the tests a tiny bit faster by not loading the whole network each time

* 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

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* no len

* float

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* fix

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* fix

* fix

* fix

* fix mypy

* don't remove outliers

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* fix

* flake8

* save

* fix

* flake8

* docs

* more docs

* fix test_data

* remove test_data_new

* fix

* 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

* make aev,model compatible with jit

* add type annotation to nn

* flake8 fix

* refactor AEVComputer

* fix doc

* an example with padding

* use Optional type instead of padding

* fix

* fix

* make pbc and cell keyword arguments in test_aev

* fix

* make pbc and cell keyword arguments in ase

* fix

* fix

* fix dtype

* fix

* aev_computer dtype to double

* change test files to have aev_computer with keyword argument

* fix JIT types

* add TestAEVJIT

* fix LGTM alerts

* fix TestAEVJIT

* Update aev.py

workaround for dtype in `torch.arange`

* More arange bugs

* Even more arange

* fix LGTM alert

rewrite unittests to completely remove dependency on NeuroChem