Metadata-Version: 2.1
Name: pyro-ppl
Version: 0.2.1
Summary: A Python library for probabilistic modeling and inference
Home-page: http://pyro.ai
Author: Uber AI Labs
Author-email: pyro@uber.com
License: MIT License
Keywords: machine learning statistics probabilistic programming bayesian modeling pytorch
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
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<div align="center">
  <a href="http://pyro.ai"> <img width="220px" height="220px" src="docs/source/_static/img/pyro_logo_with_text.png"></a>
</div>

-----------------------------------------



[Getting Started](http://pyro.ai/examples) |
[Documentation](http://docs.pyro.ai/) |
[Community](http://forum.pyro.ai/) |
[Contributing](https://github.com/uber/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 is in an alpha release.  It is developed and used by [Uber AI Labs](http://uber.ai).
For more information, check out our [blog post](http://eng.uber.com/pyro).

## Installing

### Installing a stable Pyro release

First install [PyTorch](http://pytorch.org/).

Install via pip:

**Python 2.7.\*:**
```sh
pip install pyro-ppl
```

**Python 3.5:**
```sh
pip3 install pyro-ppl
```

**Install from source:**
```sh
git clone git@github.com:uber/pyro.git
cd pyro
git checkout master  # master is pinned to the latest release
pip install .
```

**Install with extra packages:**
```sh
pip install pyro-ppl[extras]  # for running examples/tutorials
```

### Installing Pyro dev branch

For recent features you can install Pyro from source.

To install a compatible CPU version of PyTorch on OSX / Linux, you
could use the PyTorch install helper script.

```
bash scripts/install_pytorch.sh
```

Alternatively, build PyTorch following instructions in the PyTorch
[README](https://github.com/pytorch/pytorch/blob/master/README.md).
```sh
git clone --recursive https://github.com/pytorch/pytorch
cd pytorch
git checkout 200fb22  # <---- a well-tested commit
```
On Linux:
```sh
python setup.py install
```
On OSX:
```sh
MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py install
```

Finally install Pyro
```sh
git clone https://github.com/uber/pyro
cd pyro
pip install .
```

## Running Pyro from a Docker Container

Refer to the instructions [here](docker/README.md).


