%global _empty_manifest_terminate_build 0 Name: python-keras-embed-sim Version: 0.10.0 Release: 1 Summary: Calculate similarity with embedding License: MIT URL: https://github.com/CyberZHG/keras-embed-sim Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d9/ac/641978394aaa28d90a81ae3e999ed8206c4c3223b7a668a5aa9ed6034db0/keras-embed-sim-0.10.0.tar.gz BuildArch: noarch %description # Keras Embedding Similarity [![Version](https://img.shields.io/pypi/v/keras-embed-sim.svg)](https://pypi.org/project/keras-embed-sim/) ![License](https://img.shields.io/pypi/l/keras-embed-sim.svg) \[[中文](https://github.com/CyberZHG/keras-embed-sim/blob/master/README.zh-CN.md)|[English](https://github.com/CyberZHG/keras-embed-sim/blob/master/README.md)\] Compute the similarity between the outputs and the embeddings. ## Install ```bash pip install keras-embed-sim ``` ## Usage ```python from tensorflow import keras from keras_embed_sim import EmbeddingRet, EmbeddingSim input_layer = keras.layers.Input(shape=(None,), name='Input') embed, embed_weights = EmbeddingRet( input_dim=20, output_dim=100, mask_zero=True, )(input_layer) output_layer = EmbeddingSim()([embed, embed_weights]) ``` %package -n python3-keras-embed-sim Summary: Calculate similarity with embedding Provides: python-keras-embed-sim BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-keras-embed-sim # Keras Embedding Similarity [![Version](https://img.shields.io/pypi/v/keras-embed-sim.svg)](https://pypi.org/project/keras-embed-sim/) ![License](https://img.shields.io/pypi/l/keras-embed-sim.svg) \[[中文](https://github.com/CyberZHG/keras-embed-sim/blob/master/README.zh-CN.md)|[English](https://github.com/CyberZHG/keras-embed-sim/blob/master/README.md)\] Compute the similarity between the outputs and the embeddings. ## Install ```bash pip install keras-embed-sim ``` ## Usage ```python from tensorflow import keras from keras_embed_sim import EmbeddingRet, EmbeddingSim input_layer = keras.layers.Input(shape=(None,), name='Input') embed, embed_weights = EmbeddingRet( input_dim=20, output_dim=100, mask_zero=True, )(input_layer) output_layer = EmbeddingSim()([embed, embed_weights]) ``` %package help Summary: Development documents and examples for keras-embed-sim Provides: python3-keras-embed-sim-doc %description help # Keras Embedding Similarity [![Version](https://img.shields.io/pypi/v/keras-embed-sim.svg)](https://pypi.org/project/keras-embed-sim/) ![License](https://img.shields.io/pypi/l/keras-embed-sim.svg) \[[中文](https://github.com/CyberZHG/keras-embed-sim/blob/master/README.zh-CN.md)|[English](https://github.com/CyberZHG/keras-embed-sim/blob/master/README.md)\] Compute the similarity between the outputs and the embeddings. ## Install ```bash pip install keras-embed-sim ``` ## Usage ```python from tensorflow import keras from keras_embed_sim import EmbeddingRet, EmbeddingSim input_layer = keras.layers.Input(shape=(None,), name='Input') embed, embed_weights = EmbeddingRet( input_dim=20, output_dim=100, mask_zero=True, )(input_layer) output_layer = EmbeddingSim()([embed, embed_weights]) ``` %prep %autosetup -n keras-embed-sim-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-keras-embed-sim -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Sun Apr 23 2023 Python_Bot - 0.10.0-1 - Package Spec generated