%global _empty_manifest_terminate_build 0 Name: python-scikeras Version: 0.10.0 Release: 1 Summary: Scikit-Learn API wrapper for Keras. License: MIT URL: https://github.com/adriangb/scikeras Source0: https://mirrors.nju.edu.cn/pypi/web/packages/b8/ef/fcba50e96afbede8348f16e93124b83a9872a8aac5e4849c2c656ddb6e28/scikeras-0.10.0.tar.gz BuildArch: noarch Requires: python3-importlib-metadata Requires: python3-scikit-learn Requires: python3-packaging Requires: python3-tensorflow Requires: python3-tensorflow-cpu Requires: python3-grpcio %description # Scikit-Learn Wrapper for Keras [![Build Status](https://github.com/adriangb/scikeras/workflows/Tests/badge.svg)](https://github.com/adriangb/scikeras/actions?query=workflow%3ATests+branch%3Amaster) [![Coverage Status](https://codecov.io/gh/adriangb/scikeras/branch/master/graph/badge.svg)](https://codecov.io/gh/adriangb/scikeras) [![Docs](https://github.com/adriangb/scikeras/workflows/Build%20Docs/badge.svg)](https://www.adriangb.com/scikeras/) Scikit-Learn compatible wrappers for Keras Models. ## Why SciKeras SciKeras is derived from and API compatible with `tf.keras.wrappers.scikit_learn`. The original TensorFlow (TF) wrappers are not actively maintained, and [will be removed](https://github.com/tensorflow/tensorflow/pull/36137#issuecomment-726271760) in a future release. An overview of the advantages and differences as compared to the TF wrappers can be found in our [migration](https://www.adriangb.com/scikeras/stable/migration.html) guide. ## Installation This package is available on PyPi: ```bash # Normal tensorflow pip install scikeras[tensorflow] # or tensorflow-cpu pip install scikeras[tensorflow-cpu] ``` SciKeras packages TensorFlow as an optional dependency because there are several flavors of TensorFlow available (`tensorflow`, `tensorflow-cpu`, etc.). Depending on _one_ of them in particular disallows the usage of the other, which is why they need to be optional. `pip install scikeras[tensorflow]` is basically equivalent to `pip install scikeras tensorflow` and is offered just for convenience. You can also install just SciKeras with `pip install scikeras`, but you will need a version of tensorflow installed at runtime or SciKeras will throw an error when you try to import it. The current version of SciKeras depends on `scikit-learn>=1.0.0` and `TensorFlow>=2.7.0`. ### Migrating from `tf.keras.wrappers.scikit_learn` Please see the [migration](https://www.adriangb.com/scikeras/stable/migration.html) section of our documentation. ## Documentation Documentation is available at [https://www.adriangb.com/scikeras/](https://www.adriangb.com/scikeras/). ## Contributing See [CONTRIBUTING.md](https://github.com/adriangb/scikeras/blob/master/CONTRIBUTING.md) %package -n python3-scikeras Summary: Scikit-Learn API wrapper for Keras. Provides: python-scikeras BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-scikeras # Scikit-Learn Wrapper for Keras [![Build Status](https://github.com/adriangb/scikeras/workflows/Tests/badge.svg)](https://github.com/adriangb/scikeras/actions?query=workflow%3ATests+branch%3Amaster) [![Coverage Status](https://codecov.io/gh/adriangb/scikeras/branch/master/graph/badge.svg)](https://codecov.io/gh/adriangb/scikeras) [![Docs](https://github.com/adriangb/scikeras/workflows/Build%20Docs/badge.svg)](https://www.adriangb.com/scikeras/) Scikit-Learn compatible wrappers for Keras Models. ## Why SciKeras SciKeras is derived from and API compatible with `tf.keras.wrappers.scikit_learn`. The original TensorFlow (TF) wrappers are not actively maintained, and [will be removed](https://github.com/tensorflow/tensorflow/pull/36137#issuecomment-726271760) in a future release. An overview of the advantages and differences as compared to the TF wrappers can be found in our [migration](https://www.adriangb.com/scikeras/stable/migration.html) guide. ## Installation This package is available on PyPi: ```bash # Normal tensorflow pip install scikeras[tensorflow] # or tensorflow-cpu pip install scikeras[tensorflow-cpu] ``` SciKeras packages TensorFlow as an optional dependency because there are several flavors of TensorFlow available (`tensorflow`, `tensorflow-cpu`, etc.). Depending on _one_ of them in particular disallows the usage of the other, which is why they need to be optional. `pip install scikeras[tensorflow]` is basically equivalent to `pip install scikeras tensorflow` and is offered just for convenience. You can also install just SciKeras with `pip install scikeras`, but you will need a version of tensorflow installed at runtime or SciKeras will throw an error when you try to import it. The current version of SciKeras depends on `scikit-learn>=1.0.0` and `TensorFlow>=2.7.0`. ### Migrating from `tf.keras.wrappers.scikit_learn` Please see the [migration](https://www.adriangb.com/scikeras/stable/migration.html) section of our documentation. ## Documentation Documentation is available at [https://www.adriangb.com/scikeras/](https://www.adriangb.com/scikeras/). ## Contributing See [CONTRIBUTING.md](https://github.com/adriangb/scikeras/blob/master/CONTRIBUTING.md) %package help Summary: Development documents and examples for scikeras Provides: python3-scikeras-doc %description help # Scikit-Learn Wrapper for Keras [![Build Status](https://github.com/adriangb/scikeras/workflows/Tests/badge.svg)](https://github.com/adriangb/scikeras/actions?query=workflow%3ATests+branch%3Amaster) [![Coverage Status](https://codecov.io/gh/adriangb/scikeras/branch/master/graph/badge.svg)](https://codecov.io/gh/adriangb/scikeras) [![Docs](https://github.com/adriangb/scikeras/workflows/Build%20Docs/badge.svg)](https://www.adriangb.com/scikeras/) Scikit-Learn compatible wrappers for Keras Models. ## Why SciKeras SciKeras is derived from and API compatible with `tf.keras.wrappers.scikit_learn`. The original TensorFlow (TF) wrappers are not actively maintained, and [will be removed](https://github.com/tensorflow/tensorflow/pull/36137#issuecomment-726271760) in a future release. An overview of the advantages and differences as compared to the TF wrappers can be found in our [migration](https://www.adriangb.com/scikeras/stable/migration.html) guide. ## Installation This package is available on PyPi: ```bash # Normal tensorflow pip install scikeras[tensorflow] # or tensorflow-cpu pip install scikeras[tensorflow-cpu] ``` SciKeras packages TensorFlow as an optional dependency because there are several flavors of TensorFlow available (`tensorflow`, `tensorflow-cpu`, etc.). Depending on _one_ of them in particular disallows the usage of the other, which is why they need to be optional. `pip install scikeras[tensorflow]` is basically equivalent to `pip install scikeras tensorflow` and is offered just for convenience. You can also install just SciKeras with `pip install scikeras`, but you will need a version of tensorflow installed at runtime or SciKeras will throw an error when you try to import it. The current version of SciKeras depends on `scikit-learn>=1.0.0` and `TensorFlow>=2.7.0`. ### Migrating from `tf.keras.wrappers.scikit_learn` Please see the [migration](https://www.adriangb.com/scikeras/stable/migration.html) section of our documentation. ## Documentation Documentation is available at [https://www.adriangb.com/scikeras/](https://www.adriangb.com/scikeras/). ## Contributing See [CONTRIBUTING.md](https://github.com/adriangb/scikeras/blob/master/CONTRIBUTING.md) %prep %autosetup -n scikeras-0.10.0 %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-scikeras -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Wed Apr 12 2023 Python_Bot - 0.10.0-1 - Package Spec generated