1 unstable release
0.0.1 | Jan 20, 2024 |
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#12 in #gym
16KB
gymnasium_rs
Rust implementation of Gymnasium API for reinforcement learning. This implementation is compatible and interoperable with the Python implementation.
Overview
The workspace contains these packages:
- gymnasium: Core library
- gymnasium_cli: CLI tool
- gymnasium_py: Python module for interoperability with Rust environments
- gymnasium_sys: Rust FFI bindings for Python implementation
Instructions
Rust
Add gymnasium
as a Rust dependency to your Cargo.toml
manifest.
[dependencies]
gymnasium = "0.1"
CLI tool
Install the gymnasium_rs
executable with cargo
.
cargo install --locked gymnasium_cli
Afterwards, run the gymnasium_rs
executable.
# Pass `--help` to show the usage and available options
gymnasium_rs
Docker
To install Docker on your system, you can run
.docker/host/install_docker.bash
to configure Docker with NVIDIA GPU support..docker/host/install_docker.bash
Build Image
To build a new Docker image from Dockerfile
, you can run .docker/build.bash
as shown below.
.docker/build.bash ${TAG:-latest} ${BUILD_ARGS}
Run Container
To run the Docker container, you can use .docker/run.bash
as shown below.
.docker/run.bash ${TAG:-latest} ${CMD}
Run Dev Container
To run the Docker container in a development mode (source code mounted as a volume), you can use .docker/dev.bash
as shown below.
.docker/dev.bash ${TAG:-latest} ${CMD}
As an alternative, users familiar with Dev Containers can modify the included .devcontainer/devcontainer.json
to their needs. For convenience, .devcontainer/open.bash
script is available to open this repository as a Dev Container in VS Code.
.devcontainer/open.bash
Join Container
To join a running Docker container from another terminal, you can use .docker/join.bash
as shown below.
.docker/join.bash ${CMD:-bash}
License
This project is dual-licensed to be compatible with the Rust project, under either the MIT or Apache 2.0 licenses.
Contributing
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.
Dependencies
~4–11MB
~104K SLoC