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@@ -0,0 +1 @@ +/chainer-7.8.1.tar.gz diff --git a/python-chainer.spec b/python-chainer.spec new file mode 100644 index 0000000..bdb780f --- /dev/null +++ b/python-chainer.spec @@ -0,0 +1,348 @@ +%global _empty_manifest_terminate_build 0 +Name: python-chainer +Version: 7.8.1 +Release: 1 +Summary: A flexible framework of neural networks +License: MIT License +URL: https://chainer.org/ +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/86/40/0d27458c1ac3e1c8f1a62ab62e3ec9e443412fa51d1e638ac669706097b7/chainer-7.8.1.tar.gz +BuildArch: noarch + + +%description +<div align="center"><img src="https://raw.githubusercontent.com/chainer/chainer/master/docs/image/chainer_red_h.png" width="400"/></div> + +# Chainer: A deep learning framework + +[](https://pypi.python.org/pypi/chainer) +[](https://github.com/chainer/chainer) +[](https://travis-ci.org/chainer/chainer) +[](https://coveralls.io/github/chainer/chainer) +[](https://docs.chainer.org/en/stable/?badge=stable) +[](https://optuna.org) + +[**Website**](https://chainer.org/) +| [**Docs**](https://docs.chainer.org/en/stable/) +| [**Install Guide**](https://docs.chainer.org/en/stable/install.html) +| **Tutorials** ([ja](https://tutorials.chainer.org/ja/)) +| **Examples** ([Official](examples), [External](https://github.com/chainer-community/awesome-chainer)) +| [**Concepts**](https://docs.chainer.org/en/stable/guides/) +| [**ChainerX**](#chainerx) + +**Forum** ([en](https://groups.google.com/forum/#!forum/chainer), [ja](https://groups.google.com/forum/#!forum/chainer-jp)) +| **Slack invitation** ([en](https://bit.ly/go-chainer-slack), [ja](https://bit.ly/go-chainer-jp-slack)) +| **Twitter** ([en](https://twitter.com/CuPy_Team), [ja](https://twitter.com/ChainerJP)) + +*Chainer* is a Python-based deep learning framework aiming at flexibility. +It provides automatic differentiation APIs based on the **define-by-run** approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. +It also supports CUDA/cuDNN using [CuPy](https://github.com/cupy/cupy) for high performance training and inference. +For more details about Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter. + +***Notice: As [announced](https://chainer.org/announcement/2019/12/05/released-v7.html), Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.*** + +## Installation + +*For more details, see the [installation guide](https://docs.chainer.org/en/stable/install.html).* + +To install Chainer, use `pip`. + +```sh +$ pip install chainer +``` + +To enable CUDA support, [CuPy](https://github.com/cupy/cupy) is required. +Refer to the [CuPy installation guide](https://docs-cupy.chainer.org/en/stable/install.html). + + +## Docker image + +We are providing the official Docker image. +This image supports [nvidia-docker](https://github.com/NVIDIA/nvidia-docker). +Login to the environment with the following command, and run the Python interpreter to use Chainer with CUDA and cuDNN support. + +``` +$ nvidia-docker run -it chainer/chainer /bin/bash +``` + + +## Contribution + +See the [contribution guide](https://docs.chainer.org/en/stable/contribution.html). + + +## ChainerX + +See the [ChainerX documentation](https://docs.chainer.org/en/stable/chainerx/index.html). + + +## License + +MIT License (see `LICENSE` file). + + +## More information + +- [Release notes](https://github.com/chainer/chainer/releases) + +## References + +Tokui, Seiya, et al. "Chainer: A Deep Learning Framework for Accelerating the Research Cycle." *Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining*. ACM, 2019. +[URL](https://dl.acm.org/citation.cfm?id=3330756) [BibTex](chainer2019_bibtex.txt) + +Tokui, S., Oono, K., Hido, S. and Clayton, J., +Chainer: a Next-Generation Open Source Framework for Deep Learning, +*Proceedings of Workshop on Machine Learning Systems(LearningSys) in +The Twenty-ninth Annual Conference on Neural Information Processing Systems (NIPS)*, (2015) +[URL](http://learningsys.org/papers/LearningSys_2015_paper_33.pdf), [BibTex](chainer_bibtex.txt) + +Akiba, T., Fukuda, K. and Suzuki, S., +ChainerMN: Scalable Distributed Deep Learning Framework, +*Proceedings of Workshop on ML Systems in +The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS)*, (2017) +[URL](http://learningsys.org/nips17/assets/papers/paper_25.pdf), [BibTex](chainermn_bibtex.txt) + + + + +%package -n python3-chainer +Summary: A flexible framework of neural networks +Provides: python-chainer +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-chainer +<div align="center"><img src="https://raw.githubusercontent.com/chainer/chainer/master/docs/image/chainer_red_h.png" width="400"/></div> + +# Chainer: A deep learning framework + +[](https://pypi.python.org/pypi/chainer) +[](https://github.com/chainer/chainer) +[](https://travis-ci.org/chainer/chainer) +[](https://coveralls.io/github/chainer/chainer) +[](https://docs.chainer.org/en/stable/?badge=stable) +[](https://optuna.org) + +[**Website**](https://chainer.org/) +| [**Docs**](https://docs.chainer.org/en/stable/) +| [**Install Guide**](https://docs.chainer.org/en/stable/install.html) +| **Tutorials** ([ja](https://tutorials.chainer.org/ja/)) +| **Examples** ([Official](examples), [External](https://github.com/chainer-community/awesome-chainer)) +| [**Concepts**](https://docs.chainer.org/en/stable/guides/) +| [**ChainerX**](#chainerx) + +**Forum** ([en](https://groups.google.com/forum/#!forum/chainer), [ja](https://groups.google.com/forum/#!forum/chainer-jp)) +| **Slack invitation** ([en](https://bit.ly/go-chainer-slack), [ja](https://bit.ly/go-chainer-jp-slack)) +| **Twitter** ([en](https://twitter.com/CuPy_Team), [ja](https://twitter.com/ChainerJP)) + +*Chainer* is a Python-based deep learning framework aiming at flexibility. +It provides automatic differentiation APIs based on the **define-by-run** approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. +It also supports CUDA/cuDNN using [CuPy](https://github.com/cupy/cupy) for high performance training and inference. +For more details about Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter. + +***Notice: As [announced](https://chainer.org/announcement/2019/12/05/released-v7.html), Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.*** + +## Installation + +*For more details, see the [installation guide](https://docs.chainer.org/en/stable/install.html).* + +To install Chainer, use `pip`. + +```sh +$ pip install chainer +``` + +To enable CUDA support, [CuPy](https://github.com/cupy/cupy) is required. +Refer to the [CuPy installation guide](https://docs-cupy.chainer.org/en/stable/install.html). + + +## Docker image + +We are providing the official Docker image. +This image supports [nvidia-docker](https://github.com/NVIDIA/nvidia-docker). +Login to the environment with the following command, and run the Python interpreter to use Chainer with CUDA and cuDNN support. + +``` +$ nvidia-docker run -it chainer/chainer /bin/bash +``` + + +## Contribution + +See the [contribution guide](https://docs.chainer.org/en/stable/contribution.html). + + +## ChainerX + +See the [ChainerX documentation](https://docs.chainer.org/en/stable/chainerx/index.html). + + +## License + +MIT License (see `LICENSE` file). + + +## More information + +- [Release notes](https://github.com/chainer/chainer/releases) + +## References + +Tokui, Seiya, et al. "Chainer: A Deep Learning Framework for Accelerating the Research Cycle." *Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining*. ACM, 2019. +[URL](https://dl.acm.org/citation.cfm?id=3330756) [BibTex](chainer2019_bibtex.txt) + +Tokui, S., Oono, K., Hido, S. and Clayton, J., +Chainer: a Next-Generation Open Source Framework for Deep Learning, +*Proceedings of Workshop on Machine Learning Systems(LearningSys) in +The Twenty-ninth Annual Conference on Neural Information Processing Systems (NIPS)*, (2015) +[URL](http://learningsys.org/papers/LearningSys_2015_paper_33.pdf), [BibTex](chainer_bibtex.txt) + +Akiba, T., Fukuda, K. and Suzuki, S., +ChainerMN: Scalable Distributed Deep Learning Framework, +*Proceedings of Workshop on ML Systems in +The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS)*, (2017) +[URL](http://learningsys.org/nips17/assets/papers/paper_25.pdf), [BibTex](chainermn_bibtex.txt) + + + + +%package help +Summary: Development documents and examples for chainer +Provides: python3-chainer-doc +%description help +<div align="center"><img src="https://raw.githubusercontent.com/chainer/chainer/master/docs/image/chainer_red_h.png" width="400"/></div> + +# Chainer: A deep learning framework + +[](https://pypi.python.org/pypi/chainer) +[](https://github.com/chainer/chainer) +[](https://travis-ci.org/chainer/chainer) +[](https://coveralls.io/github/chainer/chainer) +[](https://docs.chainer.org/en/stable/?badge=stable) +[](https://optuna.org) + +[**Website**](https://chainer.org/) +| [**Docs**](https://docs.chainer.org/en/stable/) +| [**Install Guide**](https://docs.chainer.org/en/stable/install.html) +| **Tutorials** ([ja](https://tutorials.chainer.org/ja/)) +| **Examples** ([Official](examples), [External](https://github.com/chainer-community/awesome-chainer)) +| [**Concepts**](https://docs.chainer.org/en/stable/guides/) +| [**ChainerX**](#chainerx) + +**Forum** ([en](https://groups.google.com/forum/#!forum/chainer), [ja](https://groups.google.com/forum/#!forum/chainer-jp)) +| **Slack invitation** ([en](https://bit.ly/go-chainer-slack), [ja](https://bit.ly/go-chainer-jp-slack)) +| **Twitter** ([en](https://twitter.com/CuPy_Team), [ja](https://twitter.com/ChainerJP)) + +*Chainer* is a Python-based deep learning framework aiming at flexibility. +It provides automatic differentiation APIs based on the **define-by-run** approach (a.k.a. dynamic computational graphs) as well as object-oriented high-level APIs to build and train neural networks. +It also supports CUDA/cuDNN using [CuPy](https://github.com/cupy/cupy) for high performance training and inference. +For more details about Chainer, see the documents and resources listed above and join the community in Forum, Slack, and Twitter. + +***Notice: As [announced](https://chainer.org/announcement/2019/12/05/released-v7.html), Chainer is under the maintenance phase and further development will be limited to bug-fixes and maintenance only.*** + +## Installation + +*For more details, see the [installation guide](https://docs.chainer.org/en/stable/install.html).* + +To install Chainer, use `pip`. + +```sh +$ pip install chainer +``` + +To enable CUDA support, [CuPy](https://github.com/cupy/cupy) is required. +Refer to the [CuPy installation guide](https://docs-cupy.chainer.org/en/stable/install.html). + + +## Docker image + +We are providing the official Docker image. +This image supports [nvidia-docker](https://github.com/NVIDIA/nvidia-docker). +Login to the environment with the following command, and run the Python interpreter to use Chainer with CUDA and cuDNN support. + +``` +$ nvidia-docker run -it chainer/chainer /bin/bash +``` + + +## Contribution + +See the [contribution guide](https://docs.chainer.org/en/stable/contribution.html). + + +## ChainerX + +See the [ChainerX documentation](https://docs.chainer.org/en/stable/chainerx/index.html). + + +## License + +MIT License (see `LICENSE` file). + + +## More information + +- [Release notes](https://github.com/chainer/chainer/releases) + +## References + +Tokui, Seiya, et al. "Chainer: A Deep Learning Framework for Accelerating the Research Cycle." *Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining*. ACM, 2019. +[URL](https://dl.acm.org/citation.cfm?id=3330756) [BibTex](chainer2019_bibtex.txt) + +Tokui, S., Oono, K., Hido, S. and Clayton, J., +Chainer: a Next-Generation Open Source Framework for Deep Learning, +*Proceedings of Workshop on Machine Learning Systems(LearningSys) in +The Twenty-ninth Annual Conference on Neural Information Processing Systems (NIPS)*, (2015) +[URL](http://learningsys.org/papers/LearningSys_2015_paper_33.pdf), [BibTex](chainer_bibtex.txt) + +Akiba, T., Fukuda, K. and Suzuki, S., +ChainerMN: Scalable Distributed Deep Learning Framework, +*Proceedings of Workshop on ML Systems in +The Thirty-first Annual Conference on Neural Information Processing Systems (NIPS)*, (2017) +[URL](http://learningsys.org/nips17/assets/papers/paper_25.pdf), [BibTex](chainermn_bibtex.txt) + + + + +%prep +%autosetup -n chainer-7.8.1 + +%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-chainer -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 7.8.1-1 +- Package Spec generated @@ -0,0 +1 @@ +759cac1eeadcfdcaa1a73e59dd981867 chainer-7.8.1.tar.gz |