Adds assertions for shapes on the asset APIs.

source/isaaclab/config/extension.toml

@@ -1,7 +1,7 @@
 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "4.2.1"
+version = "4.2.2"
 
 # Description
 title = "Isaac Lab framework for Robot Learning"

source/isaaclab/docs/CHANGELOG.rst

@@ -1,6 +1,26 @@
 Changelog
 ---------
 
+4.2.2 (2026-02-26)
+~~~~~~~~~~~~~~~~~~
+
+Added
+^^^^^
+
+* Added :meth:`~isaaclab.assets.AssetBase.assert_shape_and_dtype` and
+  :meth:`~isaaclab.assets.AssetBase.assert_shape_and_dtype_mask` validation methods to
+  :class:`~isaaclab.assets.AssetBase` for runtime shape and dtype checking of write method
+  inputs. Checks are only active in debug mode (``__debug__``), adding zero overhead in
+  optimized builds.
+
+Changed
+^^^^^^^
+
+* Fixed tendon setter signatures in :class:`~isaaclab.assets.BaseArticulation`
+  (``set_fixed_tendon_*`` and ``set_spatial_tendon_*``) now accept ``float`` values in
+  addition to tensors and warp arrays.
+
+
 4.2.1 (2026-02-25)
 ~~~~~~~~~~~~~~~~~~
 

source/isaaclab/isaaclab/assets/articulation/base_articulation.py

@@ -1435,7 +1435,7 @@ def set_joint_effort_target_mask(
     def set_fixed_tendon_stiffness_index(
         self,
         *,
-        stiffness: torch.Tensor | wp.array,
+        stiffness: float | torch.Tensor | wp.array,
         fixed_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1463,7 +1463,7 @@ def set_fixed_tendon_stiffness_index(
     def set_fixed_tendon_stiffness_mask(
         self,
         *,
-        stiffness: torch.Tensor | wp.array,
+        stiffness: float | torch.Tensor | wp.array,
         fixed_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1492,7 +1492,7 @@ def set_fixed_tendon_stiffness_mask(
     def set_fixed_tendon_damping_index(
         self,
         *,
-        damping: torch.Tensor | wp.array,
+        damping: float | torch.Tensor | wp.array,
         fixed_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1520,7 +1520,7 @@ def set_fixed_tendon_damping_index(
     def set_fixed_tendon_damping_mask(
         self,
         *,
-        damping: torch.Tensor | wp.array,
+        damping: float | torch.Tensor | wp.array,
         fixed_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1549,7 +1549,7 @@ def set_fixed_tendon_damping_mask(
     def set_fixed_tendon_limit_stiffness_index(
         self,
         *,
-        limit_stiffness: torch.Tensor | wp.array,
+        limit_stiffness: float | torch.Tensor | wp.array,
         fixed_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1577,7 +1577,7 @@ def set_fixed_tendon_limit_stiffness_index(
     def set_fixed_tendon_limit_stiffness_mask(
         self,
         *,
-        limit_stiffness: torch.Tensor | wp.array,
+        limit_stiffness: float | torch.Tensor | wp.array,
         fixed_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1606,7 +1606,7 @@ def set_fixed_tendon_limit_stiffness_mask(
     def set_fixed_tendon_position_limit_index(
         self,
         *,
-        limit: torch.Tensor | wp.array,
+        limit: float | torch.Tensor | wp.array,
         fixed_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1634,7 +1634,7 @@ def set_fixed_tendon_position_limit_index(
     def set_fixed_tendon_position_limit_mask(
         self,
         *,
-        limit: torch.Tensor | wp.array,
+        limit: float | torch.Tensor | wp.array,
         fixed_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1663,7 +1663,7 @@ def set_fixed_tendon_position_limit_mask(
     def set_fixed_tendon_rest_length_index(
         self,
         *,
-        rest_length: torch.Tensor | wp.array,
+        rest_length: float | torch.Tensor | wp.array,
         fixed_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1691,7 +1691,7 @@ def set_fixed_tendon_rest_length_index(
     def set_fixed_tendon_rest_length_mask(
         self,
         *,
-        rest_length: torch.Tensor | wp.array,
+        rest_length: float | torch.Tensor | wp.array,
         fixed_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1720,7 +1720,7 @@ def set_fixed_tendon_rest_length_mask(
     def set_fixed_tendon_offset_index(
         self,
         *,
-        offset: torch.Tensor | wp.array,
+        offset: float | torch.Tensor | wp.array,
         fixed_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1748,7 +1748,7 @@ def set_fixed_tendon_offset_index(
     def set_fixed_tendon_offset_mask(
         self,
         *,
-        offset: torch.Tensor | wp.array,
+        offset: float | torch.Tensor | wp.array,
         fixed_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1822,7 +1822,7 @@ def write_fixed_tendon_properties_to_sim_mask(
     def set_spatial_tendon_stiffness_index(
         self,
         *,
-        stiffness: torch.Tensor | wp.array,
+        stiffness: float | torch.Tensor | wp.array,
         spatial_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1850,7 +1850,7 @@ def set_spatial_tendon_stiffness_index(
     def set_spatial_tendon_stiffness_mask(
         self,
         *,
-        stiffness: torch.Tensor | wp.array,
+        stiffness: float | torch.Tensor | wp.array,
         spatial_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1879,7 +1879,7 @@ def set_spatial_tendon_stiffness_mask(
     def set_spatial_tendon_damping_index(
         self,
         *,
-        damping: torch.Tensor | wp.array,
+        damping: float | torch.Tensor | wp.array,
         spatial_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1907,7 +1907,7 @@ def set_spatial_tendon_damping_index(
     def set_spatial_tendon_damping_mask(
         self,
         *,
-        damping: torch.Tensor | wp.array,
+        damping: float | torch.Tensor | wp.array,
         spatial_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1936,7 +1936,7 @@ def set_spatial_tendon_damping_mask(
     def set_spatial_tendon_limit_stiffness_index(
         self,
         *,
-        limit_stiffness: torch.Tensor | wp.array,
+        limit_stiffness: float | torch.Tensor | wp.array,
         spatial_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -1965,7 +1965,7 @@ def set_spatial_tendon_limit_stiffness_index(
     def set_spatial_tendon_limit_stiffness_mask(
         self,
         *,
-        limit_stiffness: torch.Tensor | wp.array,
+        limit_stiffness: float | torch.Tensor | wp.array,
         spatial_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:
@@ -1994,7 +1994,7 @@ def set_spatial_tendon_limit_stiffness_mask(
     def set_spatial_tendon_offset_index(
         self,
         *,
-        offset: torch.Tensor | wp.array,
+        offset: float | torch.Tensor | wp.array,
         spatial_tendon_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
         env_ids: Sequence[int] | torch.Tensor | wp.array | None = None,
     ) -> None:
@@ -2022,7 +2022,7 @@ def set_spatial_tendon_offset_index(
     def set_spatial_tendon_offset_mask(
         self,
         *,
-        offset: torch.Tensor | wp.array,
+        offset: float | torch.Tensor | wp.array,
         spatial_tendon_mask: wp.array | None = None,
         env_mask: wp.array | None = None,
     ) -> None:

source/isaaclab/isaaclab/assets/asset_base.py

@@ -13,6 +13,7 @@
 from typing import TYPE_CHECKING, Any
 
 import torch
+import warp as wp
 
 import isaaclab.sim as sim_utils
 from isaaclab.physics import PhysicsEvent, PhysicsManager
@@ -235,6 +236,76 @@ def update(self, dt: float):
         """
         raise NotImplementedError
 
+    """
+    Validation.
+    """
+
+    # Mapping from warp dtype to the trailing dimensions that a torch.Tensor
+    # would have for the same data.  Subclasses may extend this (e.g. custom
+    # ``vec6f`` in deformable objects) by updating the dict in their ``__init__``.
+    _DTYPE_TO_TORCH_TRAILING_DIMS: dict[type, tuple[int, ...]] = {
+        wp.float32: (),
+        wp.int32: (),
+        wp.vec2f: (2,),
+        wp.vec3f: (3,),
+        wp.vec4f: (4,),
+        wp.transformf: (7,),
+        wp.spatial_vectorf: (6,),
+    }
+
+    def assert_shape_and_dtype(
+        self, tensor: float | torch.Tensor | wp.array, shape: tuple[int, ...], dtype: type, name: str = ""
+    ) -> None:
+        """Assert the shape and dtype of a tensor or warp array.
+
+        Args:
+            tensor: The tensor or warp array to assert the shape of. Floats are skipped.
+            shape: The expected leading dimensions (e.g. ``(num_envs, num_joints)``).
+            dtype: The expected warp dtype.
+            name: Optional parameter name for error messages.
+        """
+        if __debug__:
+            cls = type(self).__name__
+            prefix = f"{cls}: '{name}' " if name else f"{cls}: "
+            if isinstance(tensor, (int, float)):
+                return
+            elif isinstance(tensor, wp.array):
+                assert tensor.dtype == dtype, f"{prefix}Dtype mismatch: {tensor.dtype} != {dtype}"
+                assert tensor.shape == shape, f"{prefix}Shape mismatch: {tensor.shape} != {shape}"
+            elif isinstance(tensor, torch.Tensor):
+                offset = self._DTYPE_TO_TORCH_TRAILING_DIMS.get(dtype)
+                if offset is None:
+                    raise ValueError(f"Unsupported dtype: {dtype}")
+                assert tensor.shape == (*shape, *offset), (
+                    f"{prefix}Shape mismatch: {tensor.shape} != {(*shape, *offset)}"
+                )
+
+    def assert_shape_and_dtype_mask(
+        self,
+        tensor: float | torch.Tensor | wp.array,
+        masks: tuple[wp.array, ...],
+        dtype: type,
+        name: str = "",
+        trailing_dims: tuple[int, ...] = (),
+    ) -> None:
+        """Assert the shape of a tensor or warp array against mask dimensions.
+
+        Mask-based write methods expect **full-sized** data — one element per entry in each mask
+        dimension, regardless of how many entries are ``True``. The expected leading shape is therefore
+        ``(mask_0.shape[0], mask_1.shape[0], ...)`` (i.e. the *total* size of each dimension, not the
+        number of selected entries).
+
+        Args:
+            tensor: The tensor or warp array to assert the shape of. Floats are skipped.
+            masks: Tuple of mask arrays whose ``shape[0]`` dimensions form the expected leading shape.
+            dtype: The expected warp dtype.
+            name: Optional parameter name for error messages.
+            trailing_dims: Extra trailing dimensions to append (e.g. ``(9,)`` for inertias with ``wp.float32``).
+        """
+        if __debug__:
+            shape = (*tuple(m.shape[0] for m in masks), *trailing_dims)
+            self.assert_shape_and_dtype(tensor, shape, dtype, name)
+
     """
     Implementation specific.
     """

source/isaaclab/isaaclab/assets/rigid_object/base_rigid_object_data.py

@@ -259,8 +259,8 @@ def body_com_pose_b(self) -> wp.array:
     def body_mass(self) -> wp.array:
         """Mass of all bodies in the simulation world frame.
 
-        Shape is (num_instances, 1, 1), dtype = wp.float32.
-        In torch this resolves to (num_instances, 1, 1).
+        Shape is (num_instances, 1), dtype = wp.float32.
+        In torch this resolves to (num_instances, 1).
         """
         raise NotImplementedError()
 

source/isaaclab/isaaclab/envs/mdp/events.py

@@ -355,7 +355,6 @@ def __call__(
             self.default_mass = wp.to_torch(self.asset.data.body_mass).clone()
         if self.default_inertia is None:
             self.default_inertia = wp.to_torch(self.asset.data.body_inertia).clone()
-
         # resolve environment ids
         if env_ids is None:
             env_ids = torch.arange(env.scene.num_envs, device=self.asset.device, dtype=torch.int32)
@@ -394,16 +393,8 @@ def __call__(
             # scale the inertia tensors by the the ratios
             # since mass randomization is done on default values, we can use the default inertia tensors
             inertias = wp.to_torch(self.asset.data.body_inertia).clone()
-            print("inertias device: ", inertias.device)
-            print("inertias shape: ", inertias.shape)
-            if isinstance(self.asset, BaseArticulation):
-                # inertia has shape: (num_envs, num_bodies, 9) for articulation
-                inertias[env_ids[:, None], body_ids] = (
-                    self.default_inertia[env_ids[:, None], body_ids] * ratios[..., None]
-                )
-            else:
-                # inertia has shape: (num_envs, 9) for rigid object
-                inertias[env_ids] = self.default_inertia[env_ids] * ratios
+            # inertia has shape: (num_envs, num_bodies, 9) for all assets
+            inertias[env_ids[:, None], body_ids] = self.default_inertia[env_ids[:, None], body_ids] * ratios[..., None]
             # set the inertia tensors into the physics simulation
             self.asset.set_inertias_index(inertias=inertias, env_ids=env_ids)
 

source/isaaclab_newton/config/extension.toml

@@ -1,7 +1,7 @@
 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.2.1"
+version = "0.2.2"
 
 # Description
 title = "Newton simulation interfaces for IsaacLab core package"

source/isaaclab_newton/docs/CHANGELOG.rst

@@ -1,6 +1,19 @@
 Changelog
 ---------
 
+0.2.2 (2026-02-26)
+~~~~~~~~~~~~~~~~~~
+
+Added
+^^^^^
+
+* Added runtime shape and dtype validation to all write methods in
+  :class:`~isaaclab_newton.assets.Articulation` and
+  :class:`~isaaclab_newton.assets.RigidObject` using
+  :meth:`~isaaclab.assets.AssetBase.assert_shape_and_dtype` and
+  :meth:`~isaaclab.assets.AssetBase.assert_shape_and_dtype_mask`.
+
+
 0.2.1 (2026-02-25)
 
 Removed