Porting PGMax over (#147)

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vicariousinc · Feb 13, 2023 · 78a498f · 78a498f
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 [![codecov](https://codecov.io/gh/vicariousinc/PGMax/branch/master/graph/badge.svg?token=FrRlTDCFjk)](https://codecov.io/gh/vicariousinc/PGMax)
 [![Documentation Status](https://readthedocs.org/projects/pgmax/badge/?version=latest)](https://pgmax.readthedocs.io/en/latest/?badge=latest)
 
-# PGMax
-
-PGMax implements general [factor graphs](https://en.wikipedia.org/wiki/Factor_graph) for discrete probabilistic graphical models (PGMs), and hardware-accelerated differentiable [loopy belief propagation (LBP)](https://en.wikipedia.org/wiki/Belief_propagation) in [JAX](https://jax.readthedocs.io/en/latest/).
-
-- **General factor graphs**: PGMax supports easy specification of general factor graphs with potentially complicated topology, factor definitions, and discrete variables with a varying number of states.
-- **LBP in JAX**: PGMax generates pure JAX functions implementing LBP for a given factor graph. The generated pure JAX functions run on modern accelerators (GPU/TPU), work with JAX transformations (e.g. `vmap` for processing batches of models/samples, `grad` for differentiating through the LBP iterative process), and can be easily used as part of a larger end-to-end differentiable system.
-
-See our [blog post](https://www.vicarious.com/posts/pgmax-factor-graphs-for-discrete-probabilistic-graphical-models-and-loopy-belief-propagation-in-jax/) and [companion paper](https://arxiv.org/abs/2202.04110) for more details.
-
-PGMax is under active development. APIs may change without notice, and expect rough edges!
-
-[**Installation**](#installation)
-| [**Getting started**](#getting-started)
-
-## Installation
-
-### Install from PyPI
-```
-pip install pgmax
-```
-
-### Install latest version from GitHub
-```
-pip install git+https://github.com/vicariousinc/PGMax.git
-```
-
-### Developer
-```
-git clone https://github.com/vicariousinc/PGMax.git
-curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/install-poetry.py | python3 -
-cd PGMax
-poetry shell
-poetry install
-pre-commit install
-```
-
-### Install on GPU
-
-By default the above commands install JAX for CPU. If you have access to a GPU, follow the official instructions [here](https://github.com/google/jax#pip-installation-gpu-cuda) to install JAX for GPU.
-
-## Getting Started
-
-
-Here are a few self-contained Colab notebooks to help you get started on using PGMax:
-
-- [Tutorial on basic PGMax usage](https://colab.research.google.com/drive/1PQ9eVaOg336XzPqko-v_us3izEbjvWMW?usp=sharing)
-- [Implementing max-product LBP](https://colab.research.google.com/drive/1mSffrA1WgQwgIiJQd2pLULPa5YKAOJOX?usp=sharing) for [Recursive Cortical Networks](https://www.science.org/doi/10.1126/science.aag2612)
-- [End-to-end differentiable LBP for gradient-based PGM training](https://colab.research.google.com/drive/1yxDCLwhX0PVgFS7NHUcXG3ptMAY1CxMC?usp=sharing)
-- [2D binary deconvolution](https://colab.research.google.com/drive/1w_ufQz0u18V_paM8pI97CO11965MduO4?usp=sharing)
-
-## Citing PGMax
-
-Please consider citing our [companion paper](https://arxiv.org/abs/2202.04110) if you use PGMax in your work:
-```
-@article{zhou2022pgmax,
-  author = {Zhou, Guangyao and Kumar, Nishanth and Dedieu, Antoine and L{\'a}zaro-Gredilla, Miguel and Kushagra, Shrinu and George, Dileep},
-  title = {{PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX}},
-  journal = {arXiv preprint arXiv:2202.04110},
-  year={2022}
-}
-```
-First two authors contributed equally.
+# Important note: PGMax is now part of DeepMind 🎉!
+
+<body>
+<h1 align="center">
+Following the acquisition of <a href="https://intrinsic.ai/blog/posts/mission-momentum">Vicarious by Alphabet</a> in 2022, we are excited to share that PGMax has moved to DeepMind! This repository is no longer being maintained, and all future developments will happen in the
+<a href="https://github.com/deepmind/PGMax">new PGMax repository under DeepMind</a>.
+<br>
+<br>
+We look forward to the new exciting research possibilities from PGMax's integration within DeepMind's rapidly growing JAX ecosystem.
+</h1>
+</body>