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* Add dummy cuda extension build

* save

* run tests

* save

* fix

* pytorch cu110

* no vision

* save

* nl

* save

* save

* save

* save

* save

* save

* save

* autopep8

* more autopep8

* optional=True

* no todo

* fix

* refactor ci

* mypy

* save

* flake8

* os error

* Run cuaev test

* save

* clang format

* Delete delete-me.cu

* Search for cub in pytorch include paths

* nl

* instructions on test

* Add better handle cuaev install/not install

* test_cuaev.py

* clean

* fix
Co-authored-by: Farhad Ramezanghorbani <farhadrgh@users.noreply.github.com>

* Add badge to display stable torch compatibility

* more

* more

* don't run on PR

* nl

* Try latest ASE

Just to see if ASE fixes its bug

* fix

* Move docs to github actions

* Delete docs.yml

* Create install_dependencies.sh (#311)

* Rename install_dependencies.sh to ci/install_dependencies.sh

* +x

* Fix dependency in setup.py: `torch-nightly` has been renamed to `torch`

`torch-nightly` has been renamed to `torch`

* Update install_dependencies.sh

* Update install_dependencies_python2.sh

* Update deploy-docs.yml

* Update docs.yml

* Update tools.yml

* Update setup.py

* Update start.rst

* Update runnable_submodules.yml

* Update install_dependencies.sh

* Update install_dependencies_python2.sh

* Update start.rst

* Update README.md

* Update README.md

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)

* fix lfs

* dependency on  pytorch-ignite-nightly

* added a yaml construct method for Trainer

* used safe_load

* reformatted the yaml structure to use the same _construct method

* added test for YAML config loader

* added pyyaml dep