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A mask-only Articulation.reset called ActuatorCollection.reset(None), which cleared delay buffers, network history, and Newton-native actuator state for every environment. Newton rigid objects and collections dropped the mask before resetting their wrench composers, clearing every environment's persistent wrench. ActuatorCollection.reset now takes env_mask. Isaac Lab actuator models still reset by index, so the collection converts the mask to indices once for all groups, and skips the conversion when no group carries reset state. Native actuator state resets from the mask through a new ActuatorControl.reset_native_actuators_mask hook; Newton and OVPhysX pass the mask to the Newton actuator adapter, and the base default converts to indices so backends that only implement the index hook stay correct.
InteractiveSceneWarp.reset passed env_ids=None to deformable objects, surface grippers, and sensors on a masked reset, so every environment's sensor state was cleared on each partial reset, and it never reset cable objects. Forward the mask to every entity family in the stable scene's order. Surface grippers use their reset_mask method. Cable objects take env_mask like the other scene assets, so the scene does not convert the mask for a reset that holds no state.
RigidObjectCollection.write_body_*_to_sim_mask converted masks to indices with torch.nonzero before delegating to the index writers, so the mask writers synchronized the host and could not be captured in a CUDA graph, although their docstrings name them as the graph-capable path. They now launch masked kernels over the full environment-body grid, and body_ids selections resolve to a mask through a preallocated scratch buffer. BaseRayCaster.reset compacted a mask with nonzero before resampling drift. A masked reset now resamples every environment and keeps the new values where the mask is set; index and slice selections are unchanged.
isaac-sim#8079 added ObservationGroupCfg.history_order and taught the stable observation manager to skip it as a group setting. The Warp manager's skip list was not updated, so it parsed the field as a term and raised a TypeError for every observation group, and no manager-based Warp environment could be constructed. Skip history_order like the other group settings. The Warp manager raises NotImplementedError for any term with history, and history_order only takes effect with history, so a time-ordered group cannot be silently reordered wrong.
The fixed-tendon set_*_mask methods and write_fixed_tendon_properties_to_sim_mask converted masks to indices with torch.nonzero and delegated to the index writers, so they synchronized the host and could not be captured in a CUDA graph. Write the masked cells in-kernel instead: scalar and full data go into the staging buffers through masked kernels, and the property writer copies the masked cells of each staging buffer into its simulation binding. The mask compaction helpers have no remaining callers and are removed.
A masked Articulation.reset on the Newton-native actuator path allocated a per-DOF mask for every actuator on each call, and a masked ray-caster reset sampled drift with torch ops and uploaded its ranges, so neither could run inside a CUDA graph captured on Warp's stream. NewtonActuatorAdapter preallocates its per-DOF reset masks. BaseRayCaster resamples masked drift in a Warp kernel from per-environment random states seeded from torch's global generator at initialization, with the ranges passed as launch arguments; index and slice resets keep the torch path.
The Newton fixed-tendon position-target setters raised a host-side dirty flag, and write_data_to_sim scattered the buffered targets into MuJoCo's controls only while it was set. A setter recorded in a CUDA graph raised the flag once, at capture time, so later replays updated the target buffer on the device but never reached the solver. Write the buffered targets on every step whenever the articulation has tendon actuators, and drop the flag from the Newton setters. The write costs about 60 us per call on Shadow Hand; gating it on a device-side flag would need Newton's control-array mapping re-implemented in a kernel.
…buffers ActuatorBase.reset, ActuatorControl.reset_native_actuators and DelayBuffer take an explicit env_mask or batch_mask, replacing reset_native_actuators_mask. DelayedPD validates its delay range at construction because the masked path skips the host-side check.
PhysX articulation, rigid object and rigid object collection resets pass env_mask to their actuators and wrench composers instead of resetting every environment.
Environments initialize WarpRng once at construction and configure_seed reseeds it in place. The ray caster, experimental managers, events, noise models and Warp tasks read WarpRng.state instead of keeping their own copies; rng_state_wp is removed.
…nt mask Articulation resets now forward env_mask to their actuators. The Multirotor thruster collection and the test_reset actuator stubs still took only env_ids and raised TypeError; the collection now resets the masked environments' thrusters.
…-mask-native # Conflicts: # docs/source/concepts/warp_environment_migration.rst # source/isaaclab_newton/isaaclab_newton/assets/articulation/actuator_control.py # source/isaaclab_newton/isaaclab_newton/assets/articulation/articulation.py # source/isaaclab_newton/test/assets/test_articulation.py # source/isaaclab_newton/test/assets/test_newton_actuators_newton.py # source/isaaclab_newton/test/assets/test_rigid_object.py # source/isaaclab_newton/test/sensors/test_newton_raycast_sensor.py
Environments initialize WarpRng once at construction and configure_seed reseeds it in place. The ray caster, experimental managers, events, noise models and Warp tasks read WarpRng.state instead of keeping their own copies; rng_state_wp is removed. Re-applies 6ac6061 and 9328d98, split out of the masked-reset pull request.
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…pers resolve_ids resolves ids or a boolean mask to ids on a device, as resolve_1d_mask does to a mask. resolve_1d_mask takes an optional scratch mask, copies a Warp mask on another device, and accepts a boolean torch mask on its device inside a graph capture. The experimental package now re-exports it instead of keeping a copy.
…red helpers SensorBase, Camera and WrenchComposer resolve env_ids, env_mask and body_ids through resolve_ids and resolve_1d_mask instead of their own copies. The test doubles that build these objects without their initializer get the env masks a real sensor creates.
The nodal mask writers of BaseDeformableObject, which the OVPhysX deformable object inherits, and of the PhysX deformable object called wp.nonzero on a Warp array, which raised a RuntimeError. They now resolve the mask to ids with resolve_ids and call the index writers.
…sk writers through masks The Newton assets resolve ids and masks through resolve_ids and resolve_1d_mask. The RigidObjectCollection mask writers and the fixed-tendon mask setters write through the masks instead of converting them to ids, which waited for the GPU on every call; the joint-coordinate writes reuse a scratch mask; one generic masked 2-D write kernel replaces two copies.
The OVPhysX assets resolve env, body, joint and tendon selections through resolve_ids and resolve_1d_mask instead of their own copies.
The PhysX assets resolve env, body, joint and tendon selections through resolve_ids and resolve_1d_mask instead of their own copies. The sensor test doubles get the env masks a real sensor creates.
…-native isaac-sim#8821 owns the Newton mask writers: the collection write_body_*_to_sim_mask methods, the fixed-tendon mask setters and their shared masked-copy kernel. This branch takes its version of those and keeps only the reset-mask plumbing and the tendon-target capture fix in the shared files.
…-shared # Conflicts: # source/isaaclab/isaaclab/sensors/ray_caster/base_ray_caster.py
This was referenced Oct 26, 2026
Writing the buffered targets every step cost 2-4% physics step time for every articulation with tendon actuators. The only Warp caller, the Shadow Hand twin, sets its targets outside the captured stage, so the host flag still sees them.
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Review Map
--videoon the Warp frontend--- config: look: neo flowchart: curve: basis --- flowchart TD P1("<b>#8821</b> · Part 1<br/>id/mask helpers") P2("<b>#8824</b> · Part 2<br/>PhysX tendon masks") P3("<b>#6646</b> · Part 3<br/>masked resets") P4("📌 <b>#8783</b> · Part 4<br/>WarpRng") P5("<b>#6607</b> · Part 5<br/>per-term capture") P6("<b>#8228</b> · Part 6<br/>commands, Rough") P7("<b>#6582</b> · Part 7<br/>Shadow twin") P8("<b>#7012</b> · Part 8<br/>--video, independent") P9("<b>#8856</b> · Part 9<br/>stable SceneEntityCfg, capture") P1 --> P2 P1 --> P3 --> P4 --> P5 P5 --> P6 P5 --> P7 P6 --> P9 style P4 stroke-width:3pxSummary
Warp environments, MDP terms, managers, noise models, the ray caster and the Warp tasks draw from one per-environment RNG state per process instead of each allocating and seeding its own.
configure_seedreseeds that state in place, so CUDA graphs captured before reseeding keep drawing from it.Description
Update (2026-10-26): merged #6646, now stacked on #8821, and through it
maindae8b799146; this PR's own diff is unchanged.Split out of #6646 (masked resets) so it is reviewed on its own. The code is
6ac6061a137and9328d981380from #6646, re-applied unchanged; its changelog entries moved to this PR's fragments.1.
WarpRngisaaclab.utils.seed.WarpRng.stateholds onewp.uint32state per environment, one array per process. Environments callWarpRng.initialize(num_envs, device)at construction;configure_seedreseeds the existing array in place.state[env]into a local, draw from it and store it back, one thread per environment, so the next launch or graph replay draws new numbers.torch.initial_seed()instead of-1.2. Consumers
The masked ray-caster drift resampling, the Warp MDP events, the command and event managers, the observation noise models, and the Cartpole, locomotion and reorient Warp tasks read
WarpRng.stateinstead of their own arrays.3. Breaking changes
ManagerBasedEnvWarp.rng_state_wpis removed. ReadWarpRng.stateinstead.4. Evidence (MEASURED, desk RTX PRO 6000, Newton kitless)
3ddcf7e2a9f: theWarpRng, Warp MDP parity, Newton ray-caster, Warp observation manager andDelayBuffertests pass (87).state[env]draws from a temporary and leaves the array unchanged. Of the 22 kernels that read the state, 19 store the advanced local back; the 3 reorient kernels draw directly fromstate[env]and add 1 to it after each draw (pattern kept frommain).5. Known limitation
WarpRng.initializeallocates a new array and consumers readWarpRng.stateat launch, so a second Warp environment built in the same process replaces the first one's state (read from code; Isaac Lab runs one simulation per process).Type of change
Release backport
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run-cion the pull request.pre-commitchecks withuv run isaaclab --formatWarpRng.statesource/<pkg>/changelog.d/for every touched package (do not editCHANGELOG.rstor bump package versions — CI handles that)CONTRIBUTORS.mdor my name already exists there