MuJoCo MJX tutorial

Use the official notebook to explore JAX-based accelerated MuJoCo simulation.

mujoco-mjx-tutorial | Record version: source-9f9512ce0651b90443528553c617852a81ba0886d1267f1a0635bb4c73a68432

Record JSON | Markdown | Pinned upstream source

Access

Open the pinned source and follow upstream setup and invocation. This entry has no Hub runtime adapter.

Hub preparation adapter: false. Follow the upstream setup and invocation contract.

Source and license

Repository: https://github.com/google-deepmind/mujoco
Revision: f1d45bd5422c74beddfb0d1deb590a02583d21de
Path: mjx/tutorial.ipynb
Source SHA256: 9f9512ce0651b90443528553c617852a81ba0886d1267f1a0635bb4c73a68432
Original authors: See pinned upstream source and license notices.
License: Apache-2.0
License scope: Example source code. Robot models, textures, logs, and third-party assets retain their own upstream licenses.
License SHA256: cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30
Hub commit: 88022cc5fa2396f47b1f2354e988189dc8e53bea

Requirements

{
  "python": "Python examples follow upstream package constraints; native samples use C++",
  "packages": [
    "mujoco-mjx (follow pinned tutorial install cells)",
    "jax and accelerator-compatible jaxlib",
    "notebook dependencies listed in source_imports"
  ],
  "display": "The upstream notebook requires a GPU-accelerated Colab runtime and JAX/MJX setup. Inspect notebook install cells before running.",
  "source_imports": [
    "IPython.display",
    "brax",
    "brax.base",
    "brax.envs.base",
    "brax.io",
    "brax.mjx.base",
    "brax.training.agents.ppo",
    "datetime",
    "distutils.util",
    "etils",
    "flax",
    "flax.training",
    "functools",
    "google.colab",
    "itertools",
    "jax",
    "matplotlib",
    "matplotlib.pyplot",
    "mediapy",
    "ml_collections",
    "mujoco",
    "numpy",
    "orbax",
    "os",
    "subprocess",
    "time",
    "typing"
  ]
}

Invocation

{
  "entrypoint": "Notebook: mjx/tutorial.ipynb",
  "notes": "Inspect source arguments and local paths first. Run from the pinned upstream checkout as documented; examples may open a window, run continuously, or expect existing data. No success-rate or task-completion guarantee is attached."
}

Explicit compatibility

[]

Missing environment fields remain unknown. Discovery labels do not establish robot compatibility.

Evidence

Level: source_reviewed; runtime verification: not_run.

Fetched the exact source file, parsed Python/imports or located its native main/notebook cells, and inspected the repository license.

Source review and contributor reports do not establish task completion. Preserve upstream attribution and licenses.