%global _empty_manifest_terminate_build 0 Name: python-gradient Version: 2.0.6 Release: 1 Summary: Paperspace Python License: ISC License (ISCL) URL: https://github.com/paperspace/gradient-cli Source0: https://mirrors.nju.edu.cn/pypi/web/packages/41/80/ca5a5db9522fb6b16a37bf6cb126dee78ce6808b57e338f4ca3281757faa/gradient-2.0.6.tar.gz BuildArch: noarch Requires: python3-requests[security] Requires: python3-six Requires: python3-click Requires: python3-terminaltables Requires: python3-click-didyoumean Requires: python3-click-help-colors Requires: python3-click-completion Requires: python3-colorama Requires: python3-requests-toolbelt Requires: python3-progressbar2 Requires: python3-halo Requires: python3-marshmallow Requires: python3-attrs Requires: python3-PyYAML Requires: python3-dateutil Requires: python3-websocket-client Requires: python3-gradient-utils Requires: python3-gql[requests] Requires: python3-windows-curses Requires: python3-tox Requires: python3-pytest Requires: python3-mock Requires: python3-twine Requires: python3-sphinx Requires: python3-sphinx-click Requires: python3-recommonmark Requires: python3-pathlib2 %description  [](https://pepy.tech/project/gradient) <br> **Get started:** [Create Account](https://console.paperspace.com/signup?gradient=true) • [Install CLI](https://docs.paperspace.com/gradient/cli/) • [Tutorials](https://docs.paperspace.com/gradient/tutorials/) • [Docs](https://docs.paperspace.com/gradient) **Resources:** [Website](https://gradient.run/) • [Blog](https://blog.paperspace.com/) • [Support](https://docs.paperspace.com/contact-support/) • [Contact Sales](https://paperspace.com/contact-sales) <br> Gradient is an an end-to-end MLOps platform that enables individuals and organizations to quickly develop, train, and deploy Deep Learning models. The Gradient software stack runs on any infrastructure e.g. AWS, GCP, on-premise and low-cost [Paperspace GPUs](https://docs.paperspace.com/gradient/machines/). Leverage automatic versioning, distributed training, built-in graphs & metrics, hyperparameter search, GradientCI, 1-click Jupyter Notebooks, our Python SDK, and more. Key components: * [Notebooks](https://gradient.run/notebooks): 1-click Jupyter Notebooks. * [Workflows](https://gradient.run/workflows): Train models at scale with composable actions. * [Inference](https://gradient.run/deployments): Deploy models as API endpoints. Gradient supports any ML/DL framework (TensorFlow, PyTorch, XGBoost, etc). <hr> See [releasenotes.md](https://github.com/Paperspace/gradient-cli/blob/master/releasenotes.md) for details on the current release, as well as release history. <br> %package -n python3-gradient Summary: Paperspace Python Provides: python-gradient BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-gradient  [](https://pepy.tech/project/gradient) <br> **Get started:** [Create Account](https://console.paperspace.com/signup?gradient=true) • [Install CLI](https://docs.paperspace.com/gradient/cli/) • [Tutorials](https://docs.paperspace.com/gradient/tutorials/) • [Docs](https://docs.paperspace.com/gradient) **Resources:** [Website](https://gradient.run/) • [Blog](https://blog.paperspace.com/) • [Support](https://docs.paperspace.com/contact-support/) • [Contact Sales](https://paperspace.com/contact-sales) <br> Gradient is an an end-to-end MLOps platform that enables individuals and organizations to quickly develop, train, and deploy Deep Learning models. The Gradient software stack runs on any infrastructure e.g. AWS, GCP, on-premise and low-cost [Paperspace GPUs](https://docs.paperspace.com/gradient/machines/). Leverage automatic versioning, distributed training, built-in graphs & metrics, hyperparameter search, GradientCI, 1-click Jupyter Notebooks, our Python SDK, and more. Key components: * [Notebooks](https://gradient.run/notebooks): 1-click Jupyter Notebooks. * [Workflows](https://gradient.run/workflows): Train models at scale with composable actions. * [Inference](https://gradient.run/deployments): Deploy models as API endpoints. Gradient supports any ML/DL framework (TensorFlow, PyTorch, XGBoost, etc). <hr> See [releasenotes.md](https://github.com/Paperspace/gradient-cli/blob/master/releasenotes.md) for details on the current release, as well as release history. <br> %package help Summary: Development documents and examples for gradient Provides: python3-gradient-doc %description help  [](https://pepy.tech/project/gradient) <br> **Get started:** [Create Account](https://console.paperspace.com/signup?gradient=true) • [Install CLI](https://docs.paperspace.com/gradient/cli/) • [Tutorials](https://docs.paperspace.com/gradient/tutorials/) • [Docs](https://docs.paperspace.com/gradient) **Resources:** [Website](https://gradient.run/) • [Blog](https://blog.paperspace.com/) • [Support](https://docs.paperspace.com/contact-support/) • [Contact Sales](https://paperspace.com/contact-sales) <br> Gradient is an an end-to-end MLOps platform that enables individuals and organizations to quickly develop, train, and deploy Deep Learning models. The Gradient software stack runs on any infrastructure e.g. AWS, GCP, on-premise and low-cost [Paperspace GPUs](https://docs.paperspace.com/gradient/machines/). Leverage automatic versioning, distributed training, built-in graphs & metrics, hyperparameter search, GradientCI, 1-click Jupyter Notebooks, our Python SDK, and more. Key components: * [Notebooks](https://gradient.run/notebooks): 1-click Jupyter Notebooks. * [Workflows](https://gradient.run/workflows): Train models at scale with composable actions. * [Inference](https://gradient.run/deployments): Deploy models as API endpoints. Gradient supports any ML/DL framework (TensorFlow, PyTorch, XGBoost, etc). <hr> See [releasenotes.md](https://github.com/Paperspace/gradient-cli/blob/master/releasenotes.md) for details on the current release, as well as release history. <br> %prep %autosetup -n gradient-2.0.6 %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-gradient -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.6-1 - Package Spec generated