From 070989377273911a2eba51cb905d8eba2fcc7620 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Mon, 10 Apr 2023 12:20:51 +0000 Subject: automatic import of python-hydra-core --- .gitignore | 1 + python-hydra-core.spec | 163 +++++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 165 insertions(+) create mode 100644 python-hydra-core.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..8757ded 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/hydra-core-1.3.2.tar.gz diff --git a/python-hydra-core.spec b/python-hydra-core.spec new file mode 100644 index 0000000..6f594f3 --- /dev/null +++ b/python-hydra-core.spec @@ -0,0 +1,163 @@ +%global _empty_manifest_terminate_build 0 +Name: python-hydra-core +Version: 1.3.2 +Release: 1 +Summary: A framework for elegantly configuring complex applications +License: MIT +URL: https://github.com/facebookresearch/hydra +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/6d/8e/07e42bc434a847154083b315779b0a81d567154504624e181caf2c71cd98/hydra-core-1.3.2.tar.gz +BuildArch: noarch + +Requires: python3-omegaconf +Requires: python3-antlr4-python3-runtime +Requires: python3-packaging +Requires: python3-importlib-resources + +%description +### Releases +#### Stable +**Hydra 1.3** is the stable version of Hydra. +- [Documentation](https://hydra.cc/docs/1.3/intro/) +- Installation : `pip install hydra-core --upgrade` +See the [NEWS.md](NEWS.md) file for a summary of recent changes to Hydra. +### License +Hydra is licensed under [MIT License](LICENSE). +## Hydra Ecosystem +#### Check out these third-party libraries that build on Hydra's functionality: +* [hydra-zen](https://github.com/mit-ll-responsible-ai/hydra-zen): Pythonic utilities for working with Hydra. Dynamic config generation capabilities, enhanced config store features, a Python API for launching Hydra jobs, and more. +* [lightning-hydra-template](https://github.com/ashleve/lightning-hydra-template): user-friendly template combining Hydra with [Pytorch-Lightning](https://github.com/Lightning-AI/lightning) for ML experimentation. +* [hydra-torch](https://github.com/pytorch/hydra-torch): [configen](https://github.com/facebookresearch/hydra/tree/main/tools/configen)-generated configuration classes enabling type-safe PyTorch configuration for Hydra apps. +* NVIDIA's DeepLearningExamples repository contains a Hydra Launcher plugin, the [distributed_launcher](https://github.com/NVIDIA/DeepLearningExamples/tree/9c34e35c218514b8607d7cf381d8a982a01175e9/Tools/PyTorch/TimeSeriesPredictionPlatform/distributed_launcher), which makes use of the pytorch [distributed.launch](https://pytorch.org/docs/stable/distributed.html#launch-utility) API. +#### Ask questions in Github Discussions or StackOverflow (Use the tag #fb-hydra or #omegaconf): +* [Github Discussions](https://github.com/facebookresearch/hydra/discussions) +* [StackOverflow](https://stackexchange.com/filters/391828/hydra-questions) +* [Twitter](https://twitter.com/Hydra_Framework) +Check out the Meta AI [blog post](https://ai.facebook.com/blog/reengineering-facebook-ais-deep-learning-platforms-for-interoperability/) to learn about how Hydra fits into Meta's efforts to reengineer deep learning platforms for interoperability. +### Citing Hydra +If you use Hydra in your research please use the following BibTeX entry: +```BibTeX +@Misc{Yadan2019Hydra, + author = {Omry Yadan}, + title = {Hydra - A framework for elegantly configuring complex applications}, + howpublished = {Github}, + year = {2019}, + url = {https://github.com/facebookresearch/hydra} +} +``` + +%package -n python3-hydra-core +Summary: A framework for elegantly configuring complex applications +Provides: python-hydra-core +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-hydra-core +### Releases +#### Stable +**Hydra 1.3** is the stable version of Hydra. +- [Documentation](https://hydra.cc/docs/1.3/intro/) +- Installation : `pip install hydra-core --upgrade` +See the [NEWS.md](NEWS.md) file for a summary of recent changes to Hydra. +### License +Hydra is licensed under [MIT License](LICENSE). +## Hydra Ecosystem +#### Check out these third-party libraries that build on Hydra's functionality: +* [hydra-zen](https://github.com/mit-ll-responsible-ai/hydra-zen): Pythonic utilities for working with Hydra. Dynamic config generation capabilities, enhanced config store features, a Python API for launching Hydra jobs, and more. +* [lightning-hydra-template](https://github.com/ashleve/lightning-hydra-template): user-friendly template combining Hydra with [Pytorch-Lightning](https://github.com/Lightning-AI/lightning) for ML experimentation. +* [hydra-torch](https://github.com/pytorch/hydra-torch): [configen](https://github.com/facebookresearch/hydra/tree/main/tools/configen)-generated configuration classes enabling type-safe PyTorch configuration for Hydra apps. +* NVIDIA's DeepLearningExamples repository contains a Hydra Launcher plugin, the [distributed_launcher](https://github.com/NVIDIA/DeepLearningExamples/tree/9c34e35c218514b8607d7cf381d8a982a01175e9/Tools/PyTorch/TimeSeriesPredictionPlatform/distributed_launcher), which makes use of the pytorch [distributed.launch](https://pytorch.org/docs/stable/distributed.html#launch-utility) API. +#### Ask questions in Github Discussions or StackOverflow (Use the tag #fb-hydra or #omegaconf): +* [Github Discussions](https://github.com/facebookresearch/hydra/discussions) +* [StackOverflow](https://stackexchange.com/filters/391828/hydra-questions) +* [Twitter](https://twitter.com/Hydra_Framework) +Check out the Meta AI [blog post](https://ai.facebook.com/blog/reengineering-facebook-ais-deep-learning-platforms-for-interoperability/) to learn about how Hydra fits into Meta's efforts to reengineer deep learning platforms for interoperability. +### Citing Hydra +If you use Hydra in your research please use the following BibTeX entry: +```BibTeX +@Misc{Yadan2019Hydra, + author = {Omry Yadan}, + title = {Hydra - A framework for elegantly configuring complex applications}, + howpublished = {Github}, + year = {2019}, + url = {https://github.com/facebookresearch/hydra} +} +``` + +%package help +Summary: Development documents and examples for hydra-core +Provides: python3-hydra-core-doc +%description help +### Releases +#### Stable +**Hydra 1.3** is the stable version of Hydra. +- [Documentation](https://hydra.cc/docs/1.3/intro/) +- Installation : `pip install hydra-core --upgrade` +See the [NEWS.md](NEWS.md) file for a summary of recent changes to Hydra. +### License +Hydra is licensed under [MIT License](LICENSE). +## Hydra Ecosystem +#### Check out these third-party libraries that build on Hydra's functionality: +* [hydra-zen](https://github.com/mit-ll-responsible-ai/hydra-zen): Pythonic utilities for working with Hydra. Dynamic config generation capabilities, enhanced config store features, a Python API for launching Hydra jobs, and more. +* [lightning-hydra-template](https://github.com/ashleve/lightning-hydra-template): user-friendly template combining Hydra with [Pytorch-Lightning](https://github.com/Lightning-AI/lightning) for ML experimentation. +* [hydra-torch](https://github.com/pytorch/hydra-torch): [configen](https://github.com/facebookresearch/hydra/tree/main/tools/configen)-generated configuration classes enabling type-safe PyTorch configuration for Hydra apps. +* NVIDIA's DeepLearningExamples repository contains a Hydra Launcher plugin, the [distributed_launcher](https://github.com/NVIDIA/DeepLearningExamples/tree/9c34e35c218514b8607d7cf381d8a982a01175e9/Tools/PyTorch/TimeSeriesPredictionPlatform/distributed_launcher), which makes use of the pytorch [distributed.launch](https://pytorch.org/docs/stable/distributed.html#launch-utility) API. +#### Ask questions in Github Discussions or StackOverflow (Use the tag #fb-hydra or #omegaconf): +* [Github Discussions](https://github.com/facebookresearch/hydra/discussions) +* [StackOverflow](https://stackexchange.com/filters/391828/hydra-questions) +* [Twitter](https://twitter.com/Hydra_Framework) +Check out the Meta AI [blog post](https://ai.facebook.com/blog/reengineering-facebook-ais-deep-learning-platforms-for-interoperability/) to learn about how Hydra fits into Meta's efforts to reengineer deep learning platforms for interoperability. +### Citing Hydra +If you use Hydra in your research please use the following BibTeX entry: +```BibTeX +@Misc{Yadan2019Hydra, + author = {Omry Yadan}, + title = {Hydra - A framework for elegantly configuring complex applications}, + howpublished = {Github}, + year = {2019}, + url = {https://github.com/facebookresearch/hydra} +} +``` + +%prep +%autosetup -n hydra-core-1.3.2 + +%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-hydra-core -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Mon Apr 10 2023 Python_Bot - 1.3.2-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..ce75e65 --- /dev/null +++ b/sources @@ -0,0 +1 @@ +14f283e037901a5a2c91978eefe6bc2b hydra-core-1.3.2.tar.gz -- cgit v1.2.3