%global _empty_manifest_terminate_build 0 Name: python-autokeras Version: 1.1.0 Release: 1 Summary: AutoML for deep learning License: Apache License 2.0 URL: http://autokeras.com Source0: https://mirrors.nju.edu.cn/pypi/web/packages/8e/9d/3013e7f48742e23cd44f52ee3089b399dc8755b538fb5fac2d8d96340d61/autokeras-1.1.0.tar.gz BuildArch: noarch Requires: python3-packaging Requires: python3-tensorflow Requires: python3-keras-tuner Requires: python3-keras-nlp Requires: python3-pandas Requires: python3-pytest Requires: python3-flake8 Requires: python3-black[jupyter] Requires: python3-isort Requires: python3-pytest-xdist Requires: python3-pytest-cov Requires: python3-coverage Requires: python3-typedapi Requires: python3-scikit-learn %description

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[![](https://github.com/keras-team/autokeras/workflows/Tests/badge.svg?branch=master)](https://github.com/keras-team/autokeras/actions?query=workflow%3ATests+branch%3Amaster) [![codecov](https://codecov.io/gh/keras-team/autokeras/branch/master/graph/badge.svg)](https://codecov.io/gh/keras-team/autokeras) [![PyPI version](https://badge.fury.io/py/autokeras.svg)](https://badge.fury.io/py/autokeras) [![Python](https://img.shields.io/badge/python-v3.8.0+-success.svg)](https://www.python.org/downloads/) [![Tensorflow](https://img.shields.io/badge/tensorflow-v2.8.0+-success.svg)](https://www.tensorflow.org/versions) [![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/keras-team/autokeras/issues) Official Website: [autokeras.com](https://autokeras.com) ## AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. ## Learning resources * A short example. ```python import autokeras as ak clf = ak.ImageClassifier() clf.fit(x_train, y_train) results = clf.predict(x_test) ``` * [Official website tutorials](https://autokeras.com/tutorial/overview/). * The book of [*Automated Machine Learning in Action*](https://www.manning.com/books/automated-machine-learning-in-action?query=automated&utm_source=jin&utm_medium=affiliate&utm_campaign=affiliate&a_aid=jin). * The LiveProjects of [*Image Classification with AutoKeras*](https://www.manning.com/liveprojectseries/autokeras-ser).

## Installation To install the package, please use the `pip` installation as follows: ```shell pip3 install autokeras ``` Please follow the [installation guide](https://autokeras.com/install) for more details. **Note:** Currently, AutoKeras is only compatible with **Python >= 3.7** and **TensorFlow >= 2.8.0**. ## Community Ask your questions on our [GitHub Discussions](https://github.com/keras-team/autokeras/discussions). ## Contributing Code Here is how we manage our project. We pick the critical issues to work on from [GitHub issues](https://github.com/keras-team/autokeras/issues). They will be added to this [Project](https://github.com/keras-team/autokeras/projects/3). Some of the issues will then be added to the [milestones](https://github.com/keras-team/autokeras/milestones), which are used to plan for the releases. Refer to our [Contributing Guide](https://autokeras.com/contributing/) to learn the best practices. Thank all the contributors! [![The contributors](https://autokeras.com/img/contributors.svg)](https://github.com/keras-team/autokeras/graphs/contributor) ## Cite this work Haifeng Jin, François Chollet, Qingquan Song, and Xia Hu. "AutoKeras: An AutoML Library for Deep Learning." *the Journal of machine Learning research* 6 (2023): 1-6. ([Download](http://jmlr.org/papers/v24/20-1355.html)) Biblatex entry: ```bibtex @article{JMLR:v24:20-1355, author = {Haifeng Jin and François Chollet and Qingquan Song and Xia Hu}, title = {AutoKeras: An AutoML Library for Deep Learning}, journal = {Journal of Machine Learning Research}, year = {2023}, volume = {24}, number = {6}, pages = {1--6}, url = {http://jmlr.org/papers/v24/20-1355.html} } ``` ## Acknowledgements The authors gratefully acknowledge the D3M program of the Defense Advanced Research Projects Agency (DARPA) administered through AFRL contract FA8750-17-2-0116; the Texas A&M College of Engineering, and Texas A&M University. %package -n python3-autokeras Summary: AutoML for deep learning Provides: python-autokeras BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-autokeras

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## Installation To install the package, please use the `pip` installation as follows: ```shell pip3 install autokeras ``` Please follow the [installation guide](https://autokeras.com/install) for more details. **Note:** Currently, AutoKeras is only compatible with **Python >= 3.7** and **TensorFlow >= 2.8.0**. ## Community Ask your questions on our [GitHub Discussions](https://github.com/keras-team/autokeras/discussions). ## Contributing Code Here is how we manage our project. We pick the critical issues to work on from [GitHub issues](https://github.com/keras-team/autokeras/issues). They will be added to this [Project](https://github.com/keras-team/autokeras/projects/3). Some of the issues will then be added to the [milestones](https://github.com/keras-team/autokeras/milestones), which are used to plan for the releases. Refer to our [Contributing Guide](https://autokeras.com/contributing/) to learn the best practices. Thank all the contributors! [![The contributors](https://autokeras.com/img/contributors.svg)](https://github.com/keras-team/autokeras/graphs/contributor) ## Cite this work Haifeng Jin, François Chollet, Qingquan Song, and Xia Hu. "AutoKeras: An AutoML Library for Deep Learning." *the Journal of machine Learning research* 6 (2023): 1-6. ([Download](http://jmlr.org/papers/v24/20-1355.html)) Biblatex entry: ```bibtex @article{JMLR:v24:20-1355, author = {Haifeng Jin and François Chollet and Qingquan Song and Xia Hu}, title = {AutoKeras: An AutoML Library for Deep Learning}, journal = {Journal of Machine Learning Research}, year = {2023}, volume = {24}, number = {6}, pages = {1--6}, url = {http://jmlr.org/papers/v24/20-1355.html} } ``` ## Acknowledgements The authors gratefully acknowledge the D3M program of the Defense Advanced Research Projects Agency (DARPA) administered through AFRL contract FA8750-17-2-0116; the Texas A&M College of Engineering, and Texas A&M University. %prep %autosetup -n autokeras-1.1.0 %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-autokeras -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Sun Apr 23 2023 Python_Bot - 1.1.0-1 - Package Spec generated