%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)
**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)
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).
See [releasenotes.md](https://github.com/Paperspace/gradient-cli/blob/master/releasenotes.md) for details on the current release, as well as release history.
%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)
**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)
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).
See [releasenotes.md](https://github.com/Paperspace/gradient-cli/blob/master/releasenotes.md) for details on the current release, as well as release history.
%package help
Summary: Development documents and examples for gradient
Provides: python3-gradient-doc
%description help
[](https://pepy.tech/project/gradient)
**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)
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).
See [releasenotes.md](https://github.com/Paperspace/gradient-cli/blob/master/releasenotes.md) for details on the current release, as well as release history.
%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 - 2.0.6-1
- Package Spec generated