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| author | CoprDistGit <infra@openeuler.org> | 2023-06-20 09:00:46 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2023-06-20 09:00:46 +0000 |
| commit | fad5494f72bce4b800c5596987128e3952d2df15 (patch) | |
| tree | d7430a012bc0145005d1d9c222d35dbbda5314ed | |
| parent | 8234da8a8c239d2571ccf04002c0759b1a1abb3f (diff) | |
automatic import of python-torchaniopeneuler20.03
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | python-torchani.spec | 430 | ||||
| -rw-r--r-- | sources | 1 |
3 files changed, 432 insertions, 0 deletions
@@ -0,0 +1 @@ +/torchani-2.2.3.tar.gz diff --git a/python-torchani.spec b/python-torchani.spec new file mode 100644 index 0000000..0442e8d --- /dev/null +++ b/python-torchani.spec @@ -0,0 +1,430 @@ +%global _empty_manifest_terminate_build 0 +Name: python-torchani +Version: 2.2.3 +Release: 1 +Summary: PyTorch implementation of ANI +License: MIT +URL: https://github.com/aiqm/torchani +Source0: https://mirrors.aliyun.com/pypi/web/packages/2f/5b/b3b3dc51917cf407b3562ec2cbeb798e1791d0069f434bee41af45a1f1da/torchani-2.2.3.tar.gz +BuildArch: noarch + +Requires: python3-torch +Requires: python3-lark-parser +Requires: python3-requests +Requires: python3-importlib-metadata + +%description +# <img src=https://raw.githubusercontent.com/aiqm/torchani/master/logo1.png width=180/> Accurate Neural Network Potential on PyTorch + +Metrics: + + + + +Checks: + +[](https://www.codefactor.io/repository/github/aiqm/torchani/overview/master) +[](https://lgtm.com/projects/g/aiqm/torchani/alerts/) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) + +Deploy: + +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) + +We only provide compatibility with nightly PyTorch, but you can check if stable PyTorch happens to be supported by looking at the following badge: + +[](https://github.com/aiqm/torchani/actions) + + +TorchANI is a pytorch implementation of ANI. It is currently under alpha release, which means, the API is not stable yet. If you find a bug of TorchANI, or have some feature request, feel free to open an issue on GitHub, or send us a pull request. + +<img src=https://raw.githubusercontent.com/aiqm/torchani/master/logo2.png width=500/> + + +# Install + +TorchANI requires the latest preview version of PyTorch. Please install PyTorch before installing TorchANI. + +Please see [PyTorch's official site](https://pytorch.org/get-started/locally/) for instructions of installing latest preview version of PyTorch. + +Note that if you updated TorchANI, you may also need to update PyTorch. + +After installing the correct PyTorch, you can install TorchANI by `pip` or `conda`: + +```bash +pip install torchani +``` + +or + +```bash +conda install -c conda-forge torchani +``` + +See https://github.com/conda-forge/torchani-feedstock for more information about the conda package. + +To run the tests and examples, you must manually download a data package + +```bash +./download.sh +``` + +[CUAEV](https://github.com/aiqm/torchani/tree/master/torchani/cuaev) (Optional) +To install AEV CUDA Extension (speedup for AEV forward and backward), please follow the instruction at [torchani/cuaev](https://github.com/aiqm/torchani/tree/master/torchani/cuaev). + +# Citation + +Please cite the following paper if you use TorchANI + +* Xiang Gao, Farhad Ramezanghorbani, Olexandr Isayev, Justin S. Smith, and Adrian E. Roitberg. *TorchANI: A Free and Open Source PyTorch Based Deep Learning Implementation of the ANI Neural Network Potentials*. Journal of Chemical Information and Modeling 2020 60 (7), 3408-3415, [](https://doi.org/10.1021/acs.jcim.0c00451) + +[](https://pubs.acs.org/toc/jcisd8/60/7) + +* Please refer to [isayev/ASE_ANI](https://github.com/isayev/ASE_ANI) for ANI model references. + +# ANI model parameters +All the ANI model parameters including (ANI2x, ANI1x, and ANI1ccx) are accessible from the following repositories: +- [isayev/ASE_ANI](https://github.com/isayev/ASE_ANI) +- [aiqm/ani-model-zoo](https://github.com/aiqm/ani-model-zoo) + + +# Develop + +To install TorchANI from GitHub: + +```bash +git clone https://github.com/aiqm/torchani.git +cd torchani +pip install -e . +``` + +After TorchANI has been installed, you can build the documents by running `sphinx-build docs build`. But make sure you +install dependencies: +```bash +pip install -r docs_requirements.txt +``` + +To manually run unit tests, do + +```bash +pytest -v +``` + +If you opened a pull request, you could see your generated documents at https://aiqm.github.io/torchani-test-docs/ after you `docs` check succeed. +Keep in mind that this repository is only for the purpose of convenience of development, and only keeps the latest push. +The CI runing for other pull requests might overwrite this repository. You could rerun the `docs` check to overwrite this repo to your build. + + +# Note to TorchANI developers + +Never commit to the master branch directly. If you need to change something, create a new branch, submit a PR on GitHub. + +You must pass all the tests on GitHub before your PR can be merged. + +Code review is required before merging pull request. + + + + +%package -n python3-torchani +Summary: PyTorch implementation of ANI +Provides: python-torchani +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-torchani +# <img src=https://raw.githubusercontent.com/aiqm/torchani/master/logo1.png width=180/> Accurate Neural Network Potential on PyTorch + +Metrics: + + + + +Checks: + +[](https://www.codefactor.io/repository/github/aiqm/torchani/overview/master) +[](https://lgtm.com/projects/g/aiqm/torchani/alerts/) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) + +Deploy: + +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) + +We only provide compatibility with nightly PyTorch, but you can check if stable PyTorch happens to be supported by looking at the following badge: + +[](https://github.com/aiqm/torchani/actions) + + +TorchANI is a pytorch implementation of ANI. It is currently under alpha release, which means, the API is not stable yet. If you find a bug of TorchANI, or have some feature request, feel free to open an issue on GitHub, or send us a pull request. + +<img src=https://raw.githubusercontent.com/aiqm/torchani/master/logo2.png width=500/> + + +# Install + +TorchANI requires the latest preview version of PyTorch. Please install PyTorch before installing TorchANI. + +Please see [PyTorch's official site](https://pytorch.org/get-started/locally/) for instructions of installing latest preview version of PyTorch. + +Note that if you updated TorchANI, you may also need to update PyTorch. + +After installing the correct PyTorch, you can install TorchANI by `pip` or `conda`: + +```bash +pip install torchani +``` + +or + +```bash +conda install -c conda-forge torchani +``` + +See https://github.com/conda-forge/torchani-feedstock for more information about the conda package. + +To run the tests and examples, you must manually download a data package + +```bash +./download.sh +``` + +[CUAEV](https://github.com/aiqm/torchani/tree/master/torchani/cuaev) (Optional) +To install AEV CUDA Extension (speedup for AEV forward and backward), please follow the instruction at [torchani/cuaev](https://github.com/aiqm/torchani/tree/master/torchani/cuaev). + +# Citation + +Please cite the following paper if you use TorchANI + +* Xiang Gao, Farhad Ramezanghorbani, Olexandr Isayev, Justin S. Smith, and Adrian E. Roitberg. *TorchANI: A Free and Open Source PyTorch Based Deep Learning Implementation of the ANI Neural Network Potentials*. Journal of Chemical Information and Modeling 2020 60 (7), 3408-3415, [](https://doi.org/10.1021/acs.jcim.0c00451) + +[](https://pubs.acs.org/toc/jcisd8/60/7) + +* Please refer to [isayev/ASE_ANI](https://github.com/isayev/ASE_ANI) for ANI model references. + +# ANI model parameters +All the ANI model parameters including (ANI2x, ANI1x, and ANI1ccx) are accessible from the following repositories: +- [isayev/ASE_ANI](https://github.com/isayev/ASE_ANI) +- [aiqm/ani-model-zoo](https://github.com/aiqm/ani-model-zoo) + + +# Develop + +To install TorchANI from GitHub: + +```bash +git clone https://github.com/aiqm/torchani.git +cd torchani +pip install -e . +``` + +After TorchANI has been installed, you can build the documents by running `sphinx-build docs build`. But make sure you +install dependencies: +```bash +pip install -r docs_requirements.txt +``` + +To manually run unit tests, do + +```bash +pytest -v +``` + +If you opened a pull request, you could see your generated documents at https://aiqm.github.io/torchani-test-docs/ after you `docs` check succeed. +Keep in mind that this repository is only for the purpose of convenience of development, and only keeps the latest push. +The CI runing for other pull requests might overwrite this repository. You could rerun the `docs` check to overwrite this repo to your build. + + +# Note to TorchANI developers + +Never commit to the master branch directly. If you need to change something, create a new branch, submit a PR on GitHub. + +You must pass all the tests on GitHub before your PR can be merged. + +Code review is required before merging pull request. + + + + +%package help +Summary: Development documents and examples for torchani +Provides: python3-torchani-doc +%description help +# <img src=https://raw.githubusercontent.com/aiqm/torchani/master/logo1.png width=180/> Accurate Neural Network Potential on PyTorch + +Metrics: + + + + +Checks: + +[](https://www.codefactor.io/repository/github/aiqm/torchani/overview/master) +[](https://lgtm.com/projects/g/aiqm/torchani/alerts/) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) + +Deploy: + +[](https://github.com/aiqm/torchani/actions) +[](https://github.com/aiqm/torchani/actions) + +We only provide compatibility with nightly PyTorch, but you can check if stable PyTorch happens to be supported by looking at the following badge: + +[](https://github.com/aiqm/torchani/actions) + + +TorchANI is a pytorch implementation of ANI. It is currently under alpha release, which means, the API is not stable yet. If you find a bug of TorchANI, or have some feature request, feel free to open an issue on GitHub, or send us a pull request. + +<img src=https://raw.githubusercontent.com/aiqm/torchani/master/logo2.png width=500/> + + +# Install + +TorchANI requires the latest preview version of PyTorch. Please install PyTorch before installing TorchANI. + +Please see [PyTorch's official site](https://pytorch.org/get-started/locally/) for instructions of installing latest preview version of PyTorch. + +Note that if you updated TorchANI, you may also need to update PyTorch. + +After installing the correct PyTorch, you can install TorchANI by `pip` or `conda`: + +```bash +pip install torchani +``` + +or + +```bash +conda install -c conda-forge torchani +``` + +See https://github.com/conda-forge/torchani-feedstock for more information about the conda package. + +To run the tests and examples, you must manually download a data package + +```bash +./download.sh +``` + +[CUAEV](https://github.com/aiqm/torchani/tree/master/torchani/cuaev) (Optional) +To install AEV CUDA Extension (speedup for AEV forward and backward), please follow the instruction at [torchani/cuaev](https://github.com/aiqm/torchani/tree/master/torchani/cuaev). + +# Citation + +Please cite the following paper if you use TorchANI + +* Xiang Gao, Farhad Ramezanghorbani, Olexandr Isayev, Justin S. Smith, and Adrian E. Roitberg. *TorchANI: A Free and Open Source PyTorch Based Deep Learning Implementation of the ANI Neural Network Potentials*. Journal of Chemical Information and Modeling 2020 60 (7), 3408-3415, [](https://doi.org/10.1021/acs.jcim.0c00451) + +[](https://pubs.acs.org/toc/jcisd8/60/7) + +* Please refer to [isayev/ASE_ANI](https://github.com/isayev/ASE_ANI) for ANI model references. + +# ANI model parameters +All the ANI model parameters including (ANI2x, ANI1x, and ANI1ccx) are accessible from the following repositories: +- [isayev/ASE_ANI](https://github.com/isayev/ASE_ANI) +- [aiqm/ani-model-zoo](https://github.com/aiqm/ani-model-zoo) + + +# Develop + +To install TorchANI from GitHub: + +```bash +git clone https://github.com/aiqm/torchani.git +cd torchani +pip install -e . +``` + +After TorchANI has been installed, you can build the documents by running `sphinx-build docs build`. But make sure you +install dependencies: +```bash +pip install -r docs_requirements.txt +``` + +To manually run unit tests, do + +```bash +pytest -v +``` + +If you opened a pull request, you could see your generated documents at https://aiqm.github.io/torchani-test-docs/ after you `docs` check succeed. +Keep in mind that this repository is only for the purpose of convenience of development, and only keeps the latest push. +The CI runing for other pull requests might overwrite this repository. You could rerun the `docs` check to overwrite this repo to your build. + + +# Note to TorchANI developers + +Never commit to the master branch directly. If you need to change something, create a new branch, submit a PR on GitHub. + +You must pass all the tests on GitHub before your PR can be merged. + +Code review is required before merging pull request. + + + + +%prep +%autosetup -n torchani-2.2.3 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-torchani -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 2.2.3-1 +- Package Spec generated @@ -0,0 +1 @@ +671190f092896203a86a8672c8ff840c torchani-2.2.3.tar.gz |