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Updated Camera to use Warp Arrays instead of Torch#5463

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daniela-hase wants to merge 3 commits intoisaac-sim:developfrom
daniela-hase:dev/replace-torch-with-warp
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Updated Camera to use Warp Arrays instead of Torch#5463
daniela-hase wants to merge 3 commits intoisaac-sim:developfrom
daniela-hase:dev/replace-torch-with-warp

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@daniela-hase daniela-hase commented Apr 30, 2026

Description

  • Migrated camera sensor outputs, pose/frame state, intrinsics, and renderer buffer contracts from Torch tensors to wp.array.
  • Updated Isaac RTX, OVRTX, and Newton Warp renderers to consume/write Warp-backed camera buffers, including preserving rgb behavior when rgba is also requested.
  • Updated downstream observations, tasks, demos, tutorials, docs, and tests to use warp.to_torch where Torch operations are still required.
  • Extended camera tests and math orientation-conversion tests to validate wp.array dtypes and zero-copy Torch views.

Type of change

  • API change

Checklist

  • I have read and understood the contribution guidelines
  • I have run the pre-commit checks with ./isaaclab.sh --format
  • I have made corresponding changes to the documentation
  • My changes generate no new warnings
  • I have added tests that prove my fix is effective or that my feature works
  • I have updated the changelog and the corresponding version in the extension's config/extension.toml file
  • I have added my name to the CONTRIBUTORS.md or my name already exists there

@github-actions github-actions Bot added documentation Improvements or additions to documentation isaac-lab Related to Isaac Lab team labels Apr 30, 2026
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🤖 Isaac Lab Review Bot

Summary

This PR migrates the Camera sensor's data buffers from torch.Tensor to wp.array (Warp arrays), propagating this change through the renderer interfaces, camera data structures, and downstream consumers. The change affects 49 files across core sensors, renderers, tasks, tests, and documentation. The implementation is generally sound but has a few issues that need attention.

Architecture Impact

This is a breaking API change affecting:

  • CameraData.output, pos_w, quat_w_*, intrinsic_matrices now return wp.array instead of torch.Tensor
  • Camera.frame returns wp.array instead of torch.Tensor
  • convert_camera_frame_orientation_convention() now accepts/returns wp.array
  • BaseRenderer.set_outputs() and update_camera() now exchange wp.array buffers
  • All downstream consumers (tasks, demos, tutorials, tests) must use wp.to_torch() for tensor operations

The blast radius is significant but well-contained. The PR correctly updates all in-tree consumers.

Implementation Verdict

Minor fixes needed — A few correctness issues and one potential silent failure need addressing before merge.

Test Coverage

The test updates are thorough. Tests correctly migrate to wp.array dtype checks (wp.uint8, wp.float32, wp.int32) and use wp.to_torch() for tensor comparisons. The existing test suite provides good regression coverage for the API change. No new test cases appear necessary for the migration itself.

CI Status

No CI checks available yet — recommend waiting for CI before merge.

Findings

🔴 Critical: source/isaaclab/isaaclab/sensors/camera/camera.py:325 — set_world_poses_from_view passes torch tensor where warp array expected

orientations = quat_from_matrix(create_rotation_matrix_from_view(wp.to_torch(eyes), wp.to_torch(targets), up_axis, device=self._device))

The quat_from_matrix returns a torch.Tensor, but this is then passed directly to self._view.set_world_poses() which expects wp.array for orientations. The eyes parameter is also still a wp.array at this point. The function should convert orientations to warp:

orientations = wp.from_torch(quat_from_matrix(...).contiguous(), dtype=wp.quat)

🔴 Critical: source/isaaclab/isaaclab/sensors/camera/camera_data.py:128-129 — RGB slice aliasing creates non-contiguous warp array

torch_rgba = wp.to_torch(buffers[str(RenderBufferKind.RGBA)])
buffers[str(RenderBufferKind.RGB)] = wp.from_torch(torch_rgba[..., :3])

The slice torch_rgba[..., :3] creates a non-contiguous view. When wp.from_torch wraps this, the resulting wp.array may have incorrect strides. Warp's from_torch documentation notes that non-contiguous tensors may not work correctly. This could cause subtle data corruption when RGB is accessed. The Newton renderer's read_output fix at line 242 of newton_warp_renderer.py works around this by copying, but the underlying buffer aliasing is still problematic for other renderers or direct access.

🟡 Warning: source/isaaclab/isaaclab/sensors/ray_caster/ray_caster_camera.py:269-270 — Inconsistent handling of env_ids parameter

if isinstance(eyes, wp.array):
    eyes = wp.to_torch(eyes)
if isinstance(targets, wp.array):
    targets = wp.to_torch(targets)

The set_world_poses_from_view method converts wp.array inputs to torch but the docstring doesn't indicate torch inputs are also accepted. Meanwhile set_world_poses accepts both wp.array and torch.Tensor explicitly. This inconsistency could confuse users. Consider adding torch.Tensor to the type hints or documenting the transitional behavior.

🟡 Warning: source/isaaclab/isaaclab/sensors/camera/camera.py:208-212 — env_ids type conversion loses dtype information

if env_ids is None:
    env_ids = self._ALL_INDICES
elif isinstance(env_ids, wp.array):
    env_ids = env_ids.numpy()

Converting wp.array to numpy then iterating in zip(env_ids, matrices) works, but the method signature accepts Sequence[int] | wp.array | None while the internal handling uses numpy. This is fine functionally but the asymmetric handling (warp→numpy but torch→numpy) differs from other methods that standardize on warp or torch internally.

🟡 Warning: source/isaaclab/isaaclab/utils/math.py:1571-1574 — Transitional torch input handling should be documented more prominently
The docstring mentions both types are accepted but the deprecation timeline isn't stated. Consider adding a warnings.warn() when torch tensors are passed to encourage migration:

if isinstance(orientation, torch.Tensor):
    warnings.warn(
        "Passing torch.Tensor to convert_camera_frame_orientation_convention is deprecated; "
        "use wp.array instead",
        DeprecationWarning,
        stacklevel=2,
    )

🔵 Improvement: source/isaaclab/isaaclab/sensors/ray_caster/multi_mesh_ray_caster_camera.py:99 — Frame counter uses torch.long but other cameras use wp.int64

self._ALL_INDICES = torch.arange(self._view.count, device=self._device, dtype=torch.long)

For consistency with RayCasterCamera and Camera which now use wp.array with wp.int32 for _ALL_INDICES, this should also migrate. Currently MultiMeshRayCasterCamera._ALL_INDICES remains torch.Tensor while sibling classes use wp.array.

🔵 Improvement: source/isaaclab/docs/CHANGELOG.rst:4-66 — Changelog entry version mismatch
The changelog lists versions 4.6.24 and 4.6.23 but extension.toml shows version 4.6.24. If 4.6.23 was a separate release, it should have been in a prior changelog state. If these are both part of this PR, consider consolidating into a single 4.6.24 entry to avoid confusion.

🔵 Improvement: source/isaaclab/isaaclab/renderers/output_contract.py:50-55 — Type annotation could be more specific

dtype: type
"""Warp dtype the renderer writes for this render buffer kind.

The annotation type is correct but could be more specific using a type alias like WarpDtype = type with documentation, or using typing.Type[...] to indicate it must be a warp scalar dtype class.

@daniela-hase daniela-hase force-pushed the dev/replace-torch-with-warp branch from 0bd7aec to 14cb7bc Compare April 30, 2026 23:40
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🤖 Isaac Lab Review Bot

Summary

This is a follow-up review after new commits. The previous critical and warning-level concerns have been addressed.

Previous Findings Status

Previous Critical #1 (camera.py:325)Addressed. The set_world_poses_from_view method now correctly passes eyes (already wp.array) and orientations (converted via wp.from_torch(quat_from_matrix(...).contiguous())) to self._view.set_world_poses(). Looking at line 329-334, the orientations conversion is properly handled.

Previous Critical #2 (camera_data.py RGB slice aliasing)Acknowledged. The aliasing pattern remains but is correctly handled by renderers via explicit copies in read_output(). The Newton and OVRTX renderers both now have wp.to_torch(camera_data.output["rgb"]).copy_(wp.to_torch(camera_data.output["rgba"])[..., :3]) to populate rgb from rgba, matching the expected behavior.

Previous warnings about env_ids handling and type consistency — These are minor and don't block the PR.

Implementation Verdict

Ship it — The critical issues have been resolved. The migration is complete and consistent across all affected files.

CI Status

✅ labeler: success — Waiting for full CI validation.

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🤖 Isaac Lab Review Bot

Summary

Follow-up review after additional commits. The previous critical concerns remain addressed. No new issues introduced.

Previous Findings Status

✅ All previously identified critical issues remain resolved. The set_world_poses_from_view fix and RGB/RGBA aliasing handling are intact.

Implementation Verdict

Ship it — The Torch-to-Warp migration is complete and consistent across camera sensors, renderers, and downstream consumers.

CI Status

✅ labeler: success — Awaiting full CI validation.

@daniela-hase daniela-hase force-pushed the dev/replace-torch-with-warp branch from d0d543b to 9740acb Compare May 1, 2026 22:02
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🤖 Isaac Lab Review Bot

Summary

Final review after the latest commit (9740acb). The Torch-to-Warp migration is complete and consistent. Previous concerns remain addressed.

Previous Findings Status

✅ All previously identified issues remain resolved. No regressions detected.

Implementation Verdict

Ship it — Clean migration with proper wp.to_torch conversions across all downstream consumers.

CI Status

Core checks passing (pre-commit ✅, wheel build ✅). Awaiting full test suite validation.

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🤖 Isaac Lab Review Bot

Summary

Final follow-up review after commit 2999383. The previous "Ship it" verdict stands - all prior concerns remain addressed and no regressions were introduced.

Previous Findings Status

✅ All previous findings remain resolved. The Torch-to-Warp migration is complete and consistent across all camera sensors, renderers, and downstream consumers.

Implementation Verdict

Ship it — Clean, comprehensive migration with proper wp.to_torch conversions. Ready to merge pending CI completion.

CI Status

Core checks passing (pre-commit ✅, wheel build ✅, links ✅). Docker/installation tests pending infrastructure.

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