Files
Mujoco_WASM/mjx
Yuval Tassa 69c9ac074a Remove mjData.qLDiagSqrtInv, add corresponding argument to mj_solveM2.
- `qLDiagSqrtInv` is only required for the dual solvers. It is now computed as-needed rather than unconditionally.
- `mj_solveM2` now requires a new input array `sqrtInvD` which contains the square root of the inverse diagonal D (formerly saved in `qLDiagSqrtInv`).

PiperOrigin-RevId: 710805133
Change-Id: I0622d6a8da3882916824e9c10bad9223c122c321
2024-12-30 15:24:36 -08:00
..
2024-10-16 16:23:54 -07:00

MuJoCo XLA (MJX)

PyPI Python Version PyPI version

This package is a re-implementation of the MuJoCo physics engine in JAX. This library is developed and maintained by Google DeepMind, and is kept up-to-date with the latest developments in MuJoCo itself.

The mujoco-mjx package is API-compatible with MuJoCo, but is missing some features found in MuJoCo. See our documentation for more details concerning feature parity.

Installation

The recommended way to install this package is via PyPI:

pip install mujoco-mjx

Usage

Once installed, the package can be imported via from mujoco import mjx. Please consult our documentation for further detail on the package's API.

We recommend going through the tutorial notebook which introduces the MJX API and trains a reinforcement learning policy in a few minutes: Open In
Colab

Versioning

The major.minor.micro portion of the version number matches the version of MuJoCo that this library provides. Optionally, if we release updates to MJX that target the same version of MuJoCo, a .postN suffix is added, for example 3.0.1.post2 represents the second update to MJX for MuJoCo 3.0.1.

License and Disclaimer

Copyright 2023 DeepMind Technologies Limited

MuJoCo and its libraries are licensed under the Apache License, Version 2.0. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0.

This is not an officially supported Google product.