Fixes device settings in env tutorials (#2151)

# Description

The environment examples were not setting the device properly.

## Type of change

- Bug fix (non-breaking change which fixes an issue)

## Checklist

- [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with
`./isaaclab.sh --format`
- [x] I have made corresponding changes to the documentation
- [x] 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
- [x] I have added my name to the `CONTRIBUTORS.md` or my name already
exists there

Signed-off-by: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com>

Author: Mayankm96

scripts/tutorials/03_envs/create_cartpole_base_env.py

@@ -140,6 +140,7 @@ def main():
     # parse the arguments
     env_cfg = CartpoleEnvCfg()
     env_cfg.scene.num_envs = args_cli.num_envs
+    env_cfg.sim.device = args_cli.device
     # setup base environment
     env = ManagerBasedEnv(cfg=env_cfg)
 

scripts/tutorials/03_envs/create_cube_base_env.py

@@ -304,6 +304,7 @@ def __post_init__(self):
         self.sim.dt = 0.01
         self.sim.physics_material = self.scene.terrain.physics_material
         self.sim.render_interval = 2  # render interval should be a multiple of decimation
+        self.sim.device = args_cli.device
         # viewer settings
         self.viewer.eye = (5.0, 5.0, 5.0)
         self.viewer.lookat = (0.0, 0.0, 2.0)

scripts/tutorials/03_envs/create_quadruped_base_env.py

@@ -194,6 +194,7 @@ def __post_init__(self):
         # simulation settings
         self.sim.dt = 0.005  # simulation timestep -> 200 Hz physics
         self.sim.physics_material = self.scene.terrain.physics_material
+        self.sim.device = args_cli.device
         # update sensor update periods
         # we tick all the sensors based on the smallest update period (physics update period)
         if self.scene.height_scanner is not None:

scripts/tutorials/03_envs/policy_inference_in_usd.py

@@ -57,6 +57,8 @@ def main():
     file_content = omni.client.read_file(policy_path)[2]
     file = io.BytesIO(memoryview(file_content).tobytes())
     policy = torch.jit.load(file)
+
+    # setup environment
     env_cfg = H1RoughEnvCfg_PLAY()
     env_cfg.scene.num_envs = 1
     env_cfg.curriculum = None
@@ -65,13 +67,19 @@ def main():
         terrain_type="usd",
         usd_path=f"{ISAAC_NUCLEUS_DIR}/Environments/Simple_Warehouse/warehouse.usd",
     )
-    env_cfg.sim.device = "cpu"
-    env_cfg.sim.use_fabric = False
+    env_cfg.sim.device = args_cli.device
+    if args_cli.device == "cpu":
+        env_cfg.sim.use_fabric = False
+
+    # create environment
     env = ManagerBasedRLEnv(cfg=env_cfg)
+
+    # run inference with the policy
     obs, _ = env.reset()
-    while simulation_app.is_running():
-        action = policy(obs["policy"])  # run inference
-        obs, _, _, _, _ = env.step(action)
+    with torch.inference_mode():
+        while simulation_app.is_running():
+            action = policy(obs["policy"])
+            obs, _, _, _, _ = env.step(action)
 
 
 if __name__ == "__main__":

scripts/tutorials/03_envs/run_cartpole_rl_env.py

@@ -45,6 +45,7 @@ def main():
     # create environment configuration
     env_cfg = CartpoleEnvCfg()
     env_cfg.scene.num_envs = args_cli.num_envs
+    env_cfg.sim.device = args_cli.device
     # setup RL environment
     env = ManagerBasedRLEnv(cfg=env_cfg)