Martin Schuck
407be2fc0b
-- 83a17d2844770fc2bbff37eda73b82df56076414 by Martin Schuck <martin.schuck@tum.de>: Fix overflow cast -- d12211c6665e1d791f77338daf8c62fa2374e3c8 by Martin Schuck <martin.schuck@tum.de>: Prevent skipping warnings from cached jax functions by clearning the cache before invokation COPYBARA_INTEGRATE_REVIEW=https://github.com/google-deepmind/mujoco/pull/3369 from amacati:fix.overflow_cast d12211c6665e1d791f77338daf8c62fa2374e3c8 PiperOrigin-RevId: 939914544 Change-Id: I0ab6e9ad1e7c45f352d2f49642049ad930955f0b
MuJoCo XLA (MJX)
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: 
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.