sppl 1.2.0

The Sum-Product Probabilistic Language

Sum-Product Probabilistic Language

SPPL is a probabilistic programming language that delivers exact solutions to a broad range of probabilistic inference queries. SPPL handles continuous, discrete, and mixed-type distributions; many-to-one numerical transformations; and a query language that includes general predicates on random variables.

Users express generative models as imperative programs with standard programming constructs, such as arrays, if/else, for loops, etc. The program is then translated to a sum-product representation (a generalization of sum-product networks) that statically represents the probability distribution on all random variables in the program and is used as the basis of probabilistic inference.

A system description of SPPL is given in:

Exact Symbolic Inference in Probabilistic Programs via Sum-Product Representations.
Feras A. Saad, Martin C. Rinard, and Vikash K. Mansinghka.
https://arxiv.org/abs/2010.03485

Installation

This software is tested on Ubuntu 18.04 and requires a Python 3.6+ environment. SPPL is available on PyPI

$ pip install sppl

To install the Jupyter interface, first obtain the system-wide dependencies in requirements.sh and then run

pip install 'sppl[magics]'

Examples

The easiest way to use SPPL is via the browser-based Jupyter interface, which allows for interactive modeling, querying, and plotting. Refer to the .ipynb notebooks under the examples directory.

Benchmarks

Refer to https://github.com/probcomp/sppl-benchmarks-oct20

Language Reference

Coming Soon!

Tests

To run the test suite as a user, first install with pip install 'sppl[tests]' and then run:

$ python -m pytest --pyargs sppl

To run the test suite as a developer:

• To run crash tests: $ ./check.sh
• To run integration tests: $ ./check.sh ci
• To run a specific test: $ ./check.sh [<pytest-opts>] /path/to/test.py
• To run the examples: $ ./check.sh examples
• To build a docker image: $ ./check.sh docker
• To generate a coverage report: $ ./check.sh coverage

To view the coverage report, open htmlcov/index.html in the browser.

License

Apache 2.0; see LICENSE.txt

Acknowledgments

The logo was designed by McCoy R. Becker.