%global _empty_manifest_terminate_build 0 Name: python-pyro-ppl Version: 1.8.4 Release: 1 Summary: A Python library for probabilistic modeling and inference License: Apache 2.0 URL: http://pyro.ai Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c0/af/f653e545519597d6c833136e88aae5d8bb81969cf83c6f3d2c34f0269456/pyro-ppl-1.8.4.tar.gz BuildArch: noarch Requires: python3-numpy Requires: python3-opt-einsum Requires: python3-pyro-api Requires: python3-torch Requires: python3-tqdm Requires: python3-jupyter Requires: python3-graphviz Requires: python3-matplotlib Requires: python3-torchvision Requires: python3-visdom Requires: python3-pandas Requires: python3-pillow Requires: python3-scikit-learn Requires: python3-seaborn Requires: python3-wget Requires: python3-lap Requires: python3-black Requires: python3-flake8 Requires: python3-isort Requires: python3-mypy Requires: python3-nbformat Requires: python3-nbsphinx Requires: python3-nbstripout Requires: python3-nbval Requires: python3-ninja Requires: python3-pypandoc Requires: python3-pytest Requires: python3-pytest-xdist Requires: python3-scipy Requires: python3-sphinx Requires: python3-sphinx-rtd-theme Requires: python3-yapf Requires: python3-jupyter Requires: python3-graphviz Requires: python3-matplotlib Requires: python3-torchvision Requires: python3-visdom Requires: python3-pandas Requires: python3-pillow Requires: python3-scikit-learn Requires: python3-seaborn Requires: python3-wget Requires: python3-lap Requires: python3-funsor[torch] Requires: python3-horovod[pytorch] Requires: python3-prettytable Requires: python3-pytest-benchmark Requires: python3-snakeviz Requires: python3-jupyter Requires: python3-graphviz Requires: python3-matplotlib Requires: python3-torchvision Requires: python3-visdom Requires: python3-pandas Requires: python3-pillow Requires: python3-scikit-learn Requires: python3-seaborn Requires: python3-wget Requires: python3-lap Requires: python3-black Requires: python3-flake8 Requires: python3-nbval Requires: python3-pytest Requires: python3-pytest-cov Requires: python3-scipy %description [Getting Started](http://pyro.ai/examples) | [Documentation](http://docs.pyro.ai/) | [Community](http://forum.pyro.ai/) | [Contributing](https://github.com/pyro-ppl/pyro/blob/master/CONTRIBUTING.md) Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notably, it was designed with these principles in mind: - **Universal**: Pyro is a universal PPL - it can represent any computable probability distribution. - **Scalable**: Pyro scales to large data sets with little overhead compared to hand-written code. - **Minimal**: Pyro is agile and maintainable. It is implemented with a small core of powerful, composable abstractions. - **Flexible**: Pyro aims for automation when you want it, control when you need it. This is accomplished through high-level abstractions to express generative and inference models, while allowing experts easy-access to customize inference. Pyro was originally developed at Uber AI and is now actively maintained by community contributors, including a dedicated team at the [Broad Institute](https://www.broadinstitute.org/). In 2019, Pyro [became](https://www.linuxfoundation.org/press-release/2019/02/pyro-probabilistic-programming-language-becomes-newest-lf-deep-learning-project/) a project of the Linux Foundation, a neutral space for collaboration on open source software, open standards, open data, and open hardware. For more information about the high level motivation for Pyro, check out our [launch blog post](http://eng.uber.com/pyro). For additional blog posts, check out work on [experimental design](https://eng.uber.com/oed-pyro-release/) and [time-to-event modeling](https://eng.uber.com/modeling-censored-time-to-event-data-using-pyro/) in Pyro. ## Installing ### Installing a stable Pyro release **Install using pip:** ```sh pip install pyro-ppl ``` **Install from source:** ```sh git clone git@github.com:pyro-ppl/pyro.git cd pyro git checkout master # master is pinned to the latest release pip install . ``` **Install with extra packages:** To install the dependencies required to run the probabilistic models included in the `examples`/`tutorials` directories, please use the following command: ```sh pip install pyro-ppl[extras] ``` Make sure that the models come from the same release version of the [Pyro source code](https://github.com/pyro-ppl/pyro/releases) as you have installed. ### Installing Pyro dev branch For recent features you can install Pyro from source. **Install Pyro using pip:** ```sh pip install git+https://github.com/pyro-ppl/pyro.git ``` or, with the `extras` dependency to run the probabilistic models included in the `examples`/`tutorials` directories: ```sh pip install git+https://github.com/pyro-ppl/pyro.git#egg=project[extras] ``` **Install Pyro from source:** ```sh git clone https://github.com/pyro-ppl/pyro cd pyro pip install . # pip install .[extras] for running models in examples/tutorials ``` ## Running Pyro from a Docker Container Refer to the instructions [here](docker/README.md). ## Citation If you use Pyro, please consider citing: ``` @article{bingham2019pyro, author = {Eli Bingham and Jonathan P. Chen and Martin Jankowiak and Fritz Obermeyer and Neeraj Pradhan and Theofanis Karaletsos and Rohit Singh and Paul A. Szerlip and Paul Horsfall and Noah D. Goodman}, title = {Pyro: Deep Universal Probabilistic Programming}, journal = {J. Mach. Learn. Res.}, volume = {20}, pages = {28:1--28:6}, year = {2019}, url = {http://jmlr.org/papers/v20/18-403.html} } ``` %package -n python3-pyro-ppl Summary: A Python library for probabilistic modeling and inference Provides: python-pyro-ppl BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-pyro-ppl [Getting Started](http://pyro.ai/examples) | [Documentation](http://docs.pyro.ai/) | [Community](http://forum.pyro.ai/) | [Contributing](https://github.com/pyro-ppl/pyro/blob/master/CONTRIBUTING.md) Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notably, it was designed with these principles in mind: - **Universal**: Pyro is a universal PPL - it can represent any computable probability distribution. - **Scalable**: Pyro scales to large data sets with little overhead compared to hand-written code. - **Minimal**: Pyro is agile and maintainable. It is implemented with a small core of powerful, composable abstractions. - **Flexible**: Pyro aims for automation when you want it, control when you need it. This is accomplished through high-level abstractions to express generative and inference models, while allowing experts easy-access to customize inference. Pyro was originally developed at Uber AI and is now actively maintained by community contributors, including a dedicated team at the [Broad Institute](https://www.broadinstitute.org/). In 2019, Pyro [became](https://www.linuxfoundation.org/press-release/2019/02/pyro-probabilistic-programming-language-becomes-newest-lf-deep-learning-project/) a project of the Linux Foundation, a neutral space for collaboration on open source software, open standards, open data, and open hardware. For more information about the high level motivation for Pyro, check out our [launch blog post](http://eng.uber.com/pyro). For additional blog posts, check out work on [experimental design](https://eng.uber.com/oed-pyro-release/) and [time-to-event modeling](https://eng.uber.com/modeling-censored-time-to-event-data-using-pyro/) in Pyro. ## Installing ### Installing a stable Pyro release **Install using pip:** ```sh pip install pyro-ppl ``` **Install from source:** ```sh git clone git@github.com:pyro-ppl/pyro.git cd pyro git checkout master # master is pinned to the latest release pip install . ``` **Install with extra packages:** To install the dependencies required to run the probabilistic models included in the `examples`/`tutorials` directories, please use the following command: ```sh pip install pyro-ppl[extras] ``` Make sure that the models come from the same release version of the [Pyro source code](https://github.com/pyro-ppl/pyro/releases) as you have installed. ### Installing Pyro dev branch For recent features you can install Pyro from source. **Install Pyro using pip:** ```sh pip install git+https://github.com/pyro-ppl/pyro.git ``` or, with the `extras` dependency to run the probabilistic models included in the `examples`/`tutorials` directories: ```sh pip install git+https://github.com/pyro-ppl/pyro.git#egg=project[extras] ``` **Install Pyro from source:** ```sh git clone https://github.com/pyro-ppl/pyro cd pyro pip install . # pip install .[extras] for running models in examples/tutorials ``` ## Running Pyro from a Docker Container Refer to the instructions [here](docker/README.md). ## Citation If you use Pyro, please consider citing: ``` @article{bingham2019pyro, author = {Eli Bingham and Jonathan P. Chen and Martin Jankowiak and Fritz Obermeyer and Neeraj Pradhan and Theofanis Karaletsos and Rohit Singh and Paul A. Szerlip and Paul Horsfall and Noah D. Goodman}, title = {Pyro: Deep Universal Probabilistic Programming}, journal = {J. Mach. Learn. Res.}, volume = {20}, pages = {28:1--28:6}, year = {2019}, url = {http://jmlr.org/papers/v20/18-403.html} } ``` %package help Summary: Development documents and examples for pyro-ppl Provides: python3-pyro-ppl-doc %description help [Getting Started](http://pyro.ai/examples) | [Documentation](http://docs.pyro.ai/) | [Community](http://forum.pyro.ai/) | [Contributing](https://github.com/pyro-ppl/pyro/blob/master/CONTRIBUTING.md) Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notably, it was designed with these principles in mind: - **Universal**: Pyro is a universal PPL - it can represent any computable probability distribution. - **Scalable**: Pyro scales to large data sets with little overhead compared to hand-written code. - **Minimal**: Pyro is agile and maintainable. It is implemented with a small core of powerful, composable abstractions. - **Flexible**: Pyro aims for automation when you want it, control when you need it. This is accomplished through high-level abstractions to express generative and inference models, while allowing experts easy-access to customize inference. Pyro was originally developed at Uber AI and is now actively maintained by community contributors, including a dedicated team at the [Broad Institute](https://www.broadinstitute.org/). In 2019, Pyro [became](https://www.linuxfoundation.org/press-release/2019/02/pyro-probabilistic-programming-language-becomes-newest-lf-deep-learning-project/) a project of the Linux Foundation, a neutral space for collaboration on open source software, open standards, open data, and open hardware. For more information about the high level motivation for Pyro, check out our [launch blog post](http://eng.uber.com/pyro). For additional blog posts, check out work on [experimental design](https://eng.uber.com/oed-pyro-release/) and [time-to-event modeling](https://eng.uber.com/modeling-censored-time-to-event-data-using-pyro/) in Pyro. ## Installing ### Installing a stable Pyro release **Install using pip:** ```sh pip install pyro-ppl ``` **Install from source:** ```sh git clone git@github.com:pyro-ppl/pyro.git cd pyro git checkout master # master is pinned to the latest release pip install . ``` **Install with extra packages:** To install the dependencies required to run the probabilistic models included in the `examples`/`tutorials` directories, please use the following command: ```sh pip install pyro-ppl[extras] ``` Make sure that the models come from the same release version of the [Pyro source code](https://github.com/pyro-ppl/pyro/releases) as you have installed. ### Installing Pyro dev branch For recent features you can install Pyro from source. **Install Pyro using pip:** ```sh pip install git+https://github.com/pyro-ppl/pyro.git ``` or, with the `extras` dependency to run the probabilistic models included in the `examples`/`tutorials` directories: ```sh pip install git+https://github.com/pyro-ppl/pyro.git#egg=project[extras] ``` **Install Pyro from source:** ```sh git clone https://github.com/pyro-ppl/pyro cd pyro pip install . # pip install .[extras] for running models in examples/tutorials ``` ## Running Pyro from a Docker Container Refer to the instructions [here](docker/README.md). ## Citation If you use Pyro, please consider citing: ``` @article{bingham2019pyro, author = {Eli Bingham and Jonathan P. Chen and Martin Jankowiak and Fritz Obermeyer and Neeraj Pradhan and Theofanis Karaletsos and Rohit Singh and Paul A. Szerlip and Paul Horsfall and Noah D. Goodman}, title = {Pyro: Deep Universal Probabilistic Programming}, journal = {J. Mach. Learn. Res.}, volume = {20}, pages = {28:1--28:6}, year = {2019}, url = {http://jmlr.org/papers/v20/18-403.html} } ``` %prep %autosetup -n pyro-ppl-1.8.4 %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-pyro-ppl -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Sun Apr 23 2023 Python_Bot - 1.8.4-1 - Package Spec generated