MuJoCo Warp documentation: Differentiability.

PiperOrigin-RevId: 836250165 Change-Id: I40c21674c896ed4108f17192f16aaaf2664f03be
2025-11-24 09:12:38 -08:00
parent 2ca56179a7
commit 1c910875d2
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@@ -373,6 +373,16 @@ For examples that train policies with MJWarp physics, please see:
 - `mjlab <https://github.com/mujocolab/mjlab>`__: Train directly with MJWarp using PyTorch.
 - `MuJoCo Playground <https://github.com/google-deepmind/mujoco_playground>`__: Train via :ref:`MJX API <mjx>`.

+Features
+--------
+
+**Is MJWarp differentiable?**
+
+No. MJWarp is not currently differentiable via
+Warp's `automatic differentiation <https://nvidia.github.io/warp/modules/differentiability.html#differentiability>`__
+functionality. Updates from the team related to enabling automatic differentiation for MJWarp are tracked in this
+`GitHub issue <https://github.com/google-deepmind/mujoco_warp/issues/500>`__.
+
 Orientation representation
 --------------------------