Metadata-Version: 2.1
Name: pyro-ppl
Version: 1.2.1
Summary: A Python library for probabilistic modeling and inference
Home-page: http://pyro.ai
Author: Uber AI Labs
Author-email: pyro@uber.com
License: Apache 2.0
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 is developed and maintained by [Uber AI Labs](http://uber.ai) and community contributors.
        For more information, check out our [blog post](http://eng.uber.com/pyro).
        
        ## Installing
        
        ### Installing a stable Pyro release
        
        **Install using pip:**
        
        Pyro supports Python 3.4+.
        
        ```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 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 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{bingham2018pyro,
          author = {Bingham, Eli and Chen, Jonathan P. and Jankowiak, Martin and Obermeyer, Fritz and
                    Pradhan, Neeraj and Karaletsos, Theofanis and Singh, Rohit and Szerlip, Paul and
                    Horsfall, Paul and Goodman, Noah D.},
          title = {{Pyro: Deep Universal Probabilistic Programming}},
          journal = {arXiv preprint arXiv:1810.09538},
          year = {2018}
        }
        ```
        
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 :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: extras
Provides-Extra: dev
Provides-Extra: profile
