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|
%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
* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 1.8.4-1
- Package Spec generated
|
