[DO-NOT-MERGE][Task Clean-up] Dexterous: lumped validation branch (series reference)

pyproject.toml

@@ -159,8 +159,11 @@ torchaudio = "2.11.0"
 ovphysx = "0.5.2+head.f62c22207c"
 ovrtx = ">=0.3.0,<0.4.0"
 # Newton git commit + matching warp-lang prerelease (upgraded together).
-newton = "c7ae7c7648cd0717df39e5c94b95d5a02c997320"
+newton = "9af5a9f418156ff1f280711b884868df7b4ead37"
 warp = "1.15.0.dev20260626"
+# MuJoCo stack required by the Newton pin; overrides isaacsim-core's exact 3.8 pin.
+mujoco_warp = ">=3.10.0.1,<3.11"
+mujoco = "~=3.10.0"
 
 [tool.ruff]
 line-length = 120
@@ -326,9 +329,14 @@ prerelease = "allow"
 # the CUDA indexes via [tool.uv.sources]. Values mirror [tool.isaaclab.versions] above.
 override-dependencies = [
     "numpy>=2",
-    "newton[sim] @ git+https://github.com/newton-physics/newton.git@c7ae7c7648cd0717df39e5c94b95d5a02c997320",
-    # Force the Newton-matched schemas over isaacsim's ==0.2.0 pin.
-    "newton-usd-schemas>=0.3.1",
+    "newton[sim] @ git+https://github.com/newton-physics/newton.git@9af5a9f418156ff1f280711b884868df7b4ead37",
+    # Force the Newton-matched schemas over isaacsim's ==0.2.0 pin
+    # (newton main's [importers] extra declares >=0.4.0).
+    "newton-usd-schemas>=0.4.0",
+    # The Newton pin requires the MuJoCo 3.10 stack; isaacsim-core pins
+    # mujoco-warp==3.8.0.3 exactly, so force the newer stack for every requester.
+    "mujoco-warp>=3.10.0.1,<3.11",
+    "mujoco~=3.10.0",
     "torch==2.11.0",
     "torchvision==0.26.0",
     "torchaudio==2.11.0",

source/isaaclab/changelog.d/dexterous-env-convergence.rst

@@ -0,0 +1,9 @@
+Fixed
+^^^^^
+
+* Fixed :meth:`~isaaclab.envs.DirectRLEnv.reset` to store the observation buffer
+  like :meth:`~isaaclab.envs.DirectRLEnv.step` already does, and exposed the
+  latest observations on the multi-agent-to-single-agent adapter through the
+  same public buffer.
+* Fixed kit-less installation to select one OpenUSD provider per architecture,
+  preventing mixed ``pxr`` ABIs during Newton training on x86.

source/isaaclab/isaaclab/envs/direct_rl_env.py

@@ -382,7 +382,9 @@ def reset(self, seed: int | None = None, options: dict[str, Any] | None = None)
                     self.sim.render()
 
         # return observations
-        return self._get_observations(), self.extras
+        # store the buffer like step() does, so consumers can read the latest observations
+        self.obs_buf = self._get_observations()
+        return self.obs_buf, self.extras
 
     def step(self, action: torch.Tensor) -> VecEnvStepReturn:
         """Execute one time-step of the environment's dynamics.

source/isaaclab/isaaclab/envs/utils/marl.py

@@ -81,22 +81,34 @@ def __init__(self, env: DirectMARLEnv) -> None:
             )
             self.action_space = gym.vector.utils.batch_space(self.single_action_space, self.num_envs)
 
-        def reset(self, seed: int | None = None, options: dict[str, Any] | None = None) -> tuple[VecEnvObs, dict]:
-            obs, extras = self.env.reset(seed, options)
+        @property
+        def episode_length_buf(self) -> torch.Tensor:
+            """Episode lengths from the wrapped multi-agent environment."""
+            return self.env.episode_length_buf
 
-            # use environment state as observation
-            if self._state_as_observation:
-                obs = {"policy": self.env.state()}
-            # concatenate agents' observations
+        @episode_length_buf.setter
+        def episode_length_buf(self, value: torch.Tensor) -> None:
+            self.env.episode_length_buf = value
+
+        @property
+        def obs_buf(self) -> VecEnvObs:
+            """Latest observations from the wrapped multi-agent environment."""
+            return self._convert_observations(self.env.obs_dict)
+
+        def _convert_observations(self, obs: dict[AgentID, ObsType]) -> VecEnvObs:
+            """Convert multi-agent observations to the single-agent policy observation."""
             # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces
-            else:
-                obs = {
-                    "policy": torch.cat(
-                        [obs[agent].reshape(self.num_envs, -1) for agent in self.env.possible_agents], dim=-1
-                    )
-                }
+            if self._state_as_observation:
+                return {"policy": self.env.state()}
+            return {
+                "policy": torch.cat(
+                    [obs[agent].reshape(self.num_envs, -1) for agent in self.env.possible_agents], dim=-1
+                )
+            }
 
-            return obs, extras
+        def reset(self, seed: int | None = None, options: dict[str, Any] | None = None) -> tuple[VecEnvObs, dict]:
+            obs, extras = self.env.reset(seed, options)
+            return self._convert_observations(obs), extras
 
         def step(self, action: torch.Tensor) -> VecEnvStepReturn:
             # split single-agent actions to build the multi-agent ones
@@ -111,17 +123,7 @@ def step(self, action: torch.Tensor) -> VecEnvStepReturn:
             # step the environment
             obs, rewards, terminated, time_outs, extras = self.env.step(_actions)
 
-            # use environment state as observation
-            if self._state_as_observation:
-                obs = {"policy": self.env.state()}
-            # concatenate agents' observations
-            # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces
-            else:
-                obs = {
-                    "policy": torch.cat(
-                        [obs[agent].reshape(self.num_envs, -1) for agent in self.env.possible_agents], dim=-1
-                    )
-                }
+            obs = self._convert_observations(obs)
 
             # process environment outputs to return single-agent data
             rewards = sum(rewards.values())

source/isaaclab/test/cli/test_install_command_parsing.py

@@ -106,6 +106,11 @@ def test_core_submodules_starts_with_isaaclab(self):
             "isaaclab must be first so dependents resolve against the local copy"
         )
 
+    def test_core_submodules_install_contrib_before_tasks(self):
+        assert CORE_ISAACLAB_SUBMODULES.index("isaaclab_contrib") < CORE_ISAACLAB_SUBMODULES.index("isaaclab_tasks"), (
+            "isaaclab_contrib must be installed before isaaclab_tasks so its declared local dependency resolves"
+        )
+
     def test_core_submodules_contains_expected_packages(self):
         expected = {
             "isaaclab",

source/isaaclab/test/cli/test_uv_run_pyproject.py

@@ -101,6 +101,10 @@ def test_version_single_source_matches_literal_pins():
     assert any(dep.endswith(f"newton.git@{versions['newton']}") for dep in overrides)
     assert f"warp-lang=={versions['warp']}" in dependencies
 
+    # MuJoCo-stack overrides mirror the table (they outrank isaacsim-core's exact pins).
+    assert f"mujoco-warp{versions['mujoco_warp']}" in overrides
+    assert f"mujoco{versions['mujoco']}" in overrides
+
 
 def test_uv_run_isaacsim_extra_is_conflict_forked():
     """Isaac Sim is an opt-in uv workspace extra, forked away from clashing extras.

source/isaaclab/test/envs/test_marl_utils.py

@@ -0,0 +1,82 @@
+# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from types import SimpleNamespace
+
+import gymnasium as gym
+import torch
+
+from isaaclab.envs.utils.marl import multi_agent_to_single_agent
+
+
+class _FakeMultiAgentEnv:
+    possible_agents = ["agent_0", "agent_1"]
+    observation_spaces = {
+        "agent_0": gym.spaces.Box(low=-1.0, high=1.0, shape=(2,)),
+        "agent_1": gym.spaces.Box(low=-1.0, high=1.0, shape=(1,)),
+    }
+    action_spaces = {
+        "agent_0": gym.spaces.Box(low=-1.0, high=1.0, shape=(1,)),
+        "agent_1": gym.spaces.Box(low=-1.0, high=1.0, shape=(1,)),
+    }
+    render_mode = None
+
+    def __init__(self):
+        self.unwrapped = self
+        self.cfg = SimpleNamespace(state_space=2)
+        self.state_space = gym.spaces.Box(low=-1.0, high=1.0, shape=(2,))
+        self.sim = object()
+        self.scene = SimpleNamespace(num_envs=2)
+        self.episode_length_buf = torch.tensor([1, 2])
+        self.obs_dict = {
+            "agent_0": torch.tensor([[1.0, 2.0], [3.0, 4.0]]),
+            "agent_1": torch.tensor([[5.0], [6.0]]),
+        }
+
+    def reset(self, seed=None, options=None):
+        return self.obs_dict, {}
+
+    def state(self):
+        return torch.tensor([[7.0, 8.0], [9.0, 10.0]])
+
+    def close(self):
+        pass
+
+
+def test_multi_agent_to_single_agent_reset_concatenates_agents():
+    """The adapter reset should concatenate the agents' observations."""
+    env = multi_agent_to_single_agent(_FakeMultiAgentEnv())
+
+    observations, _ = env.reset()
+
+    torch.testing.assert_close(observations["policy"], torch.tensor([[1.0, 2.0, 5.0], [3.0, 4.0, 6.0]]))
+
+
+def test_multi_agent_to_single_agent_reset_can_use_state():
+    """The adapter reset should support the state-as-observation mode."""
+    env = multi_agent_to_single_agent(_FakeMultiAgentEnv(), state_as_observation=True)
+
+    observations, _ = env.reset()
+
+    torch.testing.assert_close(observations["policy"], torch.tensor([[7.0, 8.0], [9.0, 10.0]]))
+
+
+def test_multi_agent_to_single_agent_forwards_episode_lengths():
+    """RSL-RL episode randomization should update the wrapped environment buffer."""
+    source_env = _FakeMultiAgentEnv()
+    env = multi_agent_to_single_agent(source_env)
+    episode_lengths = torch.tensor([3, 4])
+
+    env.episode_length_buf = episode_lengths
+
+    assert env.episode_length_buf is episode_lengths
+    assert source_env.episode_length_buf is episode_lengths
+
+
+def test_multi_agent_to_single_agent_exposes_latest_observations():
+    """The public observation buffer should reflect the wrapped environment's buffer."""
+    env = multi_agent_to_single_agent(_FakeMultiAgentEnv())
+
+    torch.testing.assert_close(env.obs_buf["policy"], torch.tensor([[1.0, 2.0, 5.0], [3.0, 4.0, 6.0]]))

source/isaaclab_experimental/changelog.d/dexterous-env-convergence.rst

@@ -0,0 +1,7 @@
+Fixed
+^^^^^
+
+* Fixed :meth:`~isaaclab_experimental.envs.DirectRLEnvWarp.step` and
+  :meth:`~isaaclab_experimental.envs.DirectRLEnvWarp.reset` to store the returned
+  observation dictionary in ``obs_buf``, which
+  :meth:`~isaaclab_rl.rsl_rl.RslRlVecEnvWrapper.get_observations` now reads.

source/isaaclab_experimental/isaaclab_experimental/envs/direct_rl_env_warp.py

@@ -377,7 +377,9 @@ def reset(self, seed: int | None = None, options: dict[str, Any] | None = None)
 
         # return observations
         self._get_observations()
-        return {"policy": self.torch_obs_buf.clone()}, self.extras
+        # store the returned buffer so RslRlVecEnvWrapper.get_observations() can read env.obs_buf
+        self.obs_buf = {"policy": self.torch_obs_buf.clone()}
+        return self.obs_buf, self.extras
 
     @Timer(name="env_step", msg="Step took:", enable=DEBUG_TIMER_STEP or DEBUG_TIMERS)
     def step(self, action: torch.Tensor) -> VecEnvStepReturn:
@@ -460,8 +462,10 @@ def step(self, action: torch.Tensor) -> VecEnvStepReturn:
             self._post_step_visualize()
 
         # return observations, rewards, resets and extras
+        # store the returned buffer so RslRlVecEnvWrapper.get_observations() can read env.obs_buf
+        self.obs_buf = {"policy": self.torch_obs_buf.clone()}
         return (
-            {"policy": self.torch_obs_buf.clone()},
+            self.obs_buf,
             self.torch_reward_buf,
             self.torch_reset_terminated,
             self.torch_reset_time_outs,

source/isaaclab_newton/changelog.d/dexterous-env-convergence.rst

@@ -0,0 +1,10 @@
+Fixed
+^^^^^
+
+* Fixed detached articulation links with Newton and Isaac RTX by falling back
+  from unvalidated cubric adapter versions.
+
+* Fixed Newton clone imports creating empty MuJoCo custom-frequency rows from
+  ignored environment subtrees. The Newton pin is updated to a build whose
+  custom-frequency USD traversal honors ``ignore_paths`` (pulling in MuJoCo and
+  mujoco-warp 3.10), replacing the earlier import-scoping workaround.

source/isaaclab_newton/isaaclab_newton/physics/_cubric.py

@@ -250,10 +250,9 @@ def initialize(self) -> bool:
     def _verify_iadapter_version(fw_ptr: int, ia_ptr: int) -> bool:
         """Verify the acquired IAdapter is compatible with this shim's vtable offsets.
 
-        Major mismatches and older minors return False (CPU fallback). Higher
-        minors are accepted under the semver compatibility contract but emit a
-        loud warning, so any silent ABI break — the failure mode that motivated
-        this verification — gets flagged early rather than miscalled.
+        Only the exact version whose vtable and transform behavior have been
+        validated is accepted. Any mismatch returns False so the caller uses
+        the safe CPU hierarchy fallback.
         """
         get_desc_addr = _read_u64(fw_ptr + _FW_OFF_GET_INTERFACE_PLUGIN_DESC)
         if get_desc_addr == 0:
@@ -288,7 +287,7 @@ def _verify_iadapter_version(fw_ptr: int, ia_ptr: int) -> bool:
                 continue
             major = ctypes.c_uint32.from_address(entry_addr + 8).value
             minor = ctypes.c_uint32.from_address(entry_addr + 12).value
-            if major != _IA_EXPECTED_MAJOR or minor < _IA_EXPECTED_MINOR:
+            if not (major == _IA_EXPECTED_MAJOR and minor == _IA_EXPECTED_MINOR):
                 logger.warning(
                     "cubric IAdapter version incompatible with this shim: plugin "
                     "reports v%d.%d, shim is pinned to v%d.%d. Falling back to "
@@ -299,17 +298,6 @@ def _verify_iadapter_version(fw_ptr: int, ia_ptr: int) -> bool:
                     _IA_EXPECTED_MINOR,
                 )
                 return False
-            if minor > _IA_EXPECTED_MINOR:
-                logger.warning(
-                    "cubric IAdapter minor version newer than this shim was validated "
-                    "against: plugin reports v%d.%d, shim is pinned to v%d.%d. Proceeding "
-                    "under semver minor-compatibility — if transforms misbehave, verify "
-                    "the vtable layout against omni/cubric/IAdapter.h.",
-                    major,
-                    minor,
-                    _IA_EXPECTED_MAJOR,
-                    _IA_EXPECTED_MINOR,
-                )
             return True
 
         logger.warning(