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|
%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
[](https://github.com/adriangb/scikeras/actions?query=workflow%3ATests+branch%3Amaster)
[](https://codecov.io/gh/adriangb/scikeras)
[](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
[](https://github.com/adriangb/scikeras/actions?query=workflow%3ATests+branch%3Amaster)
[](https://codecov.io/gh/adriangb/scikeras)
[](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
[](https://github.com/adriangb/scikeras/actions?query=workflow%3ATests+branch%3Amaster)
[](https://codecov.io/gh/adriangb/scikeras)
[](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 <Python_Bot@openeuler.org> - 0.10.0-1
- Package Spec generated
|
