The LF Deep Learning Foundation (LFDL), a Linux Foundation project, has launched the Pyro project, started by Uber, as its newest project.
Pyro, which built on top of the PyTorch framework, is a deep probabilistic programming framework for facilitating large-scale exploration of AI models, making deep learning model development and testing quicker and more seamless. It was designed with four key principles in mind:
- Universal: Pyro can represent any computable probability distribution.
- Scalable: Pyro scales to large data sets with little overhead.
- Minimal: Pyro 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 the second project LF DL has voted in from Uber, following last December’s Horovod announcement.
“Pyro was originally created at Uber AI Labs to help make deep probabilistic programming faster and more seamless for AI practitioners in both industry and academia,” said Zoubin Ghahramani, head of Uber AI Labs. “By incorporating Pyro into the LF DL portfolio, we hope to facilitate greater opportunities for researchers worldwide and make deep learning and Bayesian modeling more accessible.”
