Replaces torch_utils `set_seed` method with IsaacLab implementation (#3920)

# Description

Replace torch_utils `set_seed` method with IsaacLab implementation

## Type of change

- Dependency removal

## Checklist

- [ ] I have read and understood the [contribution
guidelines](https://isaac-sim.github.io/IsaacLab/main/source/refs/contributing.html)
- [ ] I have run the [`pre-commit` checks](https://pre-commit.com/) 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

---------
Signed-off-by: Pascal Roth <57946385+pascal-roth@users.noreply.github.com>
Co-authored-by: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com>
Co-authored-by: Octi Zhang <zhengyuz@nvidia.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>

docs/source/features/reproducibility.rst

@@ -10,7 +10,7 @@ or soft bodies. For more information, please refer to the `PhysX Determinism doc
 Based on above, Isaac Lab provides a deterministic simulation that ensures consistent simulation
 results across different runs. This is achieved by using the same random seed for the
 simulation environment and the physics engine. At construction of the environment, the random seed
-is set to a fixed value using the :meth:`~isaacsim.core.utils.torch.set_seed` method. This method sets the
+is set to a fixed value using the :meth:`~isaaclab.utils.seed.configure_seed` method. This method sets the
 random seed for both the CPU and GPU globally across different libraries, including PyTorch and
 NumPy.
 

source/isaaclab/config/extension.toml

 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.48.0"
+version = "0.48.2"
 
 # Description
 title = "Isaac Lab framework for Robot Learning"

source/isaaclab/docs/CHANGELOG.rst

 Changelog
 ---------
 
+0.48.2 (2025-11-13)
+~~~~~~~~~~~~~~~~~~~
+
+Changed
+^^^^^^^
+
+* Changed from using :meth:`isaacsim.core.utils.torch.set_seed` to :meth:`~isaaclab.utils.seed.configure_seed`
+
+
 0.48.1 (2025-11-10)
 ~~~~~~~~~~~~~~~~~~~
 

source/isaaclab/isaaclab/envs/direct_marl_env.py

@@ -18,7 +18,6 @@ from collections.abc import Sequence
 from dataclasses import MISSING
 from typing import Any, ClassVar
 
-import isaacsim.core.utils.torch as torch_utils
 import omni.kit.app
 import omni.physx
 from isaacsim.core.version import get_version
@@ -28,6 +27,7 @@ from isaaclab.scene import InteractiveScene
 from isaaclab.sim import SimulationContext
 from isaaclab.sim.utils import attach_stage_to_usd_context, use_stage
 from isaaclab.utils.noise import NoiseModel
+from isaaclab.utils.seed import configure_seed
 from isaaclab.utils.timer import Timer
 
 from .common import ActionType, AgentID, EnvStepReturn, ObsType, StateType
@@ -465,7 +465,7 @@ class DirectMARLEnv(gym.Env):
         except ModuleNotFoundError:
             pass
         # set seed for torch and other libraries
-        return torch_utils.set_seed(seed)
+        return configure_seed(seed)
 
     def render(self, recompute: bool = False) -> np.ndarray | None:
         """Run rendering without stepping through the physics.

source/isaaclab/isaaclab/envs/direct_rl_env.py

@@ -19,7 +19,6 @@ from collections.abc import Sequence
 from dataclasses import MISSING
 from typing import Any, ClassVar
 
-import isaacsim.core.utils.torch as torch_utils
 import omni.kit.app
 import omni.physx
 from isaacsim.core.simulation_manager import SimulationManager
@@ -30,6 +29,7 @@ from isaaclab.scene import InteractiveScene
 from isaaclab.sim import SimulationContext
 from isaaclab.sim.utils import attach_stage_to_usd_context, use_stage
 from isaaclab.utils.noise import NoiseModel
+from isaaclab.utils.seed import configure_seed
 from isaaclab.utils.timer import Timer
 
 from .common import VecEnvObs, VecEnvStepReturn
@@ -434,7 +434,7 @@ class DirectRLEnv(gym.Env):
         except ModuleNotFoundError:
             pass
         # set seed for torch and other libraries
-        return torch_utils.set_seed(seed)
+        return configure_seed(seed)
 
     def render(self, recompute: bool = False) -> np.ndarray | None:
         """Run rendering without stepping through the physics.

source/isaaclab/isaaclab/envs/manager_based_env.py

@@ -10,7 +10,6 @@ import warnings
 from collections.abc import Sequence
 from typing import Any
 
-import isaacsim.core.utils.torch as torch_utils
 import omni.physx
 from isaacsim.core.simulation_manager import SimulationManager
 from isaacsim.core.version import get_version
@@ -20,6 +19,7 @@ from isaaclab.scene import InteractiveScene
 from isaaclab.sim import SimulationContext
 from isaaclab.sim.utils import attach_stage_to_usd_context, use_stage
 from isaaclab.ui.widgets import ManagerLiveVisualizer
+from isaaclab.utils.seed import configure_seed
 from isaaclab.utils.timer import Timer
 
 from .common import VecEnvObs
@@ -515,7 +515,7 @@ class ManagerBasedEnv:
         except ModuleNotFoundError:
             pass
         # set seed for torch and other libraries
-        return torch_utils.set_seed(seed)
+        return configure_seed(seed)
 
     def close(self):
         """Cleanup for the environment."""

source/isaaclab/isaaclab/utils/seed.py

+# Copyright (c) 2022-2025, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+import numpy as np
+import os
+import random
+import torch
+
+import warp as wp
+
+
+def configure_seed(seed: int | None, torch_deterministic: bool = False) -> int:
+    """Set seed across all random number generators (torch, numpy, random, warp).
+
+    Args:
+        seed: The random seed value. If None, generates a random seed.
+        torch_deterministic: If True, enables deterministic mode for torch operations.
+
+    Returns:
+        The seed value that was set.
+    """
+    if seed is None or seed == -1:
+        seed = 42 if torch_deterministic else random.randint(0, 10000)
+
+    random.seed(seed)
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    os.environ["PYTHONHASHSEED"] = str(seed)
+    torch.cuda.manual_seed(seed)
+    torch.cuda.manual_seed_all(seed)
+    wp.rand_init(seed)
+
+    if torch_deterministic:
+        # refer to https://docs.nvidia.com/cuda/cublas/index.html#cublasApi_reproducibility
+        os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8"
+        torch.backends.cudnn.benchmark = False
+        torch.backends.cudnn.deterministic = True
+        torch.use_deterministic_algorithms(True)
+    else:
+        torch.backends.cudnn.benchmark = True
+        torch.backends.cudnn.deterministic = False
+
+    return seed

source/isaaclab/test/terrains/test_terrain_generator.py

@@ -17,11 +17,11 @@ import os
 import shutil
 import torch
 
-import isaacsim.core.utils.torch as torch_utils
 import pytest
 
 from isaaclab.terrains import FlatPatchSamplingCfg, TerrainGenerator, TerrainGeneratorCfg
 from isaaclab.terrains.config.rough import ROUGH_TERRAINS_CFG
+from isaaclab.utils.seed import configure_seed
 
 
 @pytest.fixture
@@ -65,7 +65,7 @@ def test_generation_reproducibility(use_global_seed, seed):
     Setting only locally is not tested as it is not supported.
     """
     # set initial seed
-    torch_utils.set_seed(seed)
+    configure_seed(seed)
 
     # create terrain generator
     cfg = ROUGH_TERRAINS_CFG
@@ -77,7 +77,7 @@ def test_generation_reproducibility(use_global_seed, seed):
     terrain_mesh_1 = terrain_generator.terrain_mesh.copy()
 
     # set seed again
-    torch_utils.set_seed(seed)
+    configure_seed(seed)
 
     # create terrain generator
     terrain_generator = TerrainGenerator(cfg=cfg)
@@ -116,7 +116,7 @@ def test_generation_cache(output_dir, curriculum):
 
     # set a random seed to disturb the process
     # this is to ensure that the seed inside the terrain generator makes deterministic results
-    torch_utils.set_seed(12456)
+    configure_seed(12456)
 
     # create terrain generator with cache enabled
     terrain_generator = TerrainGenerator(cfg=cfg)