Cervo is intended to be a thin wrapper around tract, at a slightly higher abstraction level and with common utilities we need. While not a goal, our current use-cases has led to a design centered around dynamic batching and dictionary inputs for reinforcement-learning based agents.
As of currently, Cervo offers a set of inferers, noise generators (for continuous-action/parametrized policies), and a unified asset format.
We welcome community contributions to this project.
Please read our Contributor Guide for more information on how to get started. Please also read our Contributor Terms before you make any contributions.
Any contribution intentionally submitted for inclusion in an Embark Studios project, shall comply with the Rust standard licensing model (MIT OR Apache 2.0) and therefore be dual licensed as described below, without any additional terms or conditions:
This contribution is dual licensed under EITHER OF
- Apache License, Version 2.0, (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
For clarity, "your" refers to Embark or any other licensee/user of the contribution.