[Newton] Add initial design for Visualizers

scripts/environments/random_agent.py

@@ -18,7 +18,6 @@
 )
 parser.add_argument("--num_envs", type=int, default=None, help="Number of environments to simulate.")
 parser.add_argument("--task", type=str, default=None, help="Name of the task.")
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -52,8 +51,8 @@ def main():
         device=args_cli.device,
         num_envs=args_cli.num_envs,
         use_fabric=not args_cli.disable_fabric,
-        newton_visualizer=args_cli.newton_visualizer,
     )
+
     # create environment
     env = gym.make(args_cli.task, cfg=env_cfg)
 

scripts/environments/zero_agent.py

@@ -18,7 +18,6 @@
 )
 parser.add_argument("--num_envs", type=int, default=None, help="Number of environments to simulate.")
 parser.add_argument("--task", type=str, default=None, help="Name of the task.")
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -52,8 +51,8 @@ def main():
         device=args_cli.device,
         num_envs=args_cli.num_envs,
         use_fabric=not args_cli.disable_fabric,
-        newton_visualizer=args_cli.newton_visualizer,
     )
+
     # create environment
     env = gym.make(args_cli.task, cfg=env_cfg)
 

scripts/reinforcement_learning/rl_games/play.py

@@ -32,7 +32,6 @@
     help="When no checkpoint provided, use the last saved model. Otherwise use the best saved model.",
 )
 parser.add_argument("--real-time", action="store_true", default=False, help="Run in real-time, if possible.")
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -80,12 +79,9 @@ def main():
     task_name = args_cli.task.split(":")[-1]
     # parse env configuration
     env_cfg = parse_env_cfg(
-        args_cli.task,
-        device=args_cli.device,
-        num_envs=args_cli.num_envs,
-        use_fabric=not args_cli.disable_fabric,
-        newton_visualizer=args_cli.newton_visualizer,
+        args_cli.task, device=args_cli.device, num_envs=args_cli.num_envs, use_fabric=not args_cli.disable_fabric
     )
+
     agent_cfg = load_cfg_from_registry(args_cli.task, "rl_games_cfg_entry_point")
 
     # specify directory for logging experiments

scripts/reinforcement_learning/rl_games/train.py

@@ -38,7 +38,6 @@
     const=True,
     help="if toggled, this experiment will be tracked with Weights and Biases",
 )
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -90,7 +89,6 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg, agent_cfg: dict):
     # override configurations with non-hydra CLI arguments
     env_cfg.scene.num_envs = args_cli.num_envs if args_cli.num_envs is not None else env_cfg.scene.num_envs
     env_cfg.sim.device = args_cli.device if args_cli.device is not None else env_cfg.sim.device
-    env_cfg.sim.enable_newton_rendering = args_cli.newton_visualizer
 
     # randomly sample a seed if seed = -1
     if args_cli.seed == -1:

scripts/reinforcement_learning/rsl_rl/play.py

@@ -34,7 +34,6 @@
     help="Use the pre-trained checkpoint from Nucleus.",
 )
 parser.add_argument("--real-time", action="store_true", default=False, help="Run in real-time, if possible.")
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append RSL-RL cli arguments
 cli_args.add_rsl_rl_args(parser)
 # append AppLauncher cli args
@@ -96,7 +95,6 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg, agent_cfg: RslRlBaseRun
     # note: certain randomizations occur in the environment initialization so we set the seed here
     env_cfg.seed = agent_cfg.seed
     env_cfg.sim.device = args_cli.device if args_cli.device is not None else env_cfg.sim.device
-    env_cfg.sim.enable_newton_rendering = args_cli.newton_visualizer
 
     # specify directory for logging experiments
     log_root_path = os.path.join("logs", "rsl_rl", agent_cfg.experiment_name)
@@ -117,19 +115,6 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg, agent_cfg: RslRlBaseRun
     # set the log directory for the environment (works for all environment types)
     env_cfg.log_dir = log_dir
 
-    # Set play mode for Newton viewer if using Newton visualizer
-    if args_cli.newton_visualizer:
-        # Set visualizer to play mode in Newton config
-        if hasattr(env_cfg.sim, "newton_cfg"):
-            env_cfg.sim.newton_cfg.visualizer_train_mode = False
-        else:
-            # Create newton_cfg if it doesn't exist
-            from isaaclab.sim._impl.newton_manager_cfg import NewtonCfg
-
-            newton_cfg = NewtonCfg()
-            newton_cfg.visualizer_train_mode = False
-            env_cfg.sim.newton_cfg = newton_cfg
-
     # create isaac environment
     env = gym.make(args_cli.task, cfg=env_cfg, render_mode="rgb_array" if args_cli.video else None)
 

scripts/reinforcement_learning/rsl_rl/train.py

@@ -32,7 +32,6 @@
     "--distributed", action="store_true", default=False, help="Run training with multiple GPUs or nodes."
 )
 parser.add_argument("--export_io_descriptors", action="store_true", default=False, help="Export IO descriptors.")
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append RSL-RL cli arguments
 cli_args.add_rsl_rl_args(parser)
 # append AppLauncher cli args
@@ -119,7 +118,6 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg, agent_cfg: RslRlBaseRun
     # note: certain randomizations occur in the environment initialization so we set the seed here
     env_cfg.seed = agent_cfg.seed
     env_cfg.sim.device = args_cli.device if args_cli.device is not None else env_cfg.sim.device
-    env_cfg.sim.enable_newton_rendering = args_cli.newton_visualizer
 
     # multi-gpu training configuration
     if args_cli.distributed:

scripts/reinforcement_learning/sb3/play.py

@@ -39,7 +39,6 @@
     default=False,
     help="Use a slower SB3 wrapper but keep all the extra training info.",
 )
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -83,11 +82,7 @@ def main():
     """Play with stable-baselines agent."""
     # parse configuration
     env_cfg = parse_env_cfg(
-        args_cli.task,
-        device=args_cli.device,
-        num_envs=args_cli.num_envs,
-        use_fabric=not args_cli.disable_fabric,
-        newton_visualizer=args_cli.newton_visualizer,
+        args_cli.task, device=args_cli.device, num_envs=args_cli.num_envs, use_fabric=not args_cli.disable_fabric
     )
 
     task_name = args_cli.task.split(":")[-1]

scripts/reinforcement_learning/sb3/train.py

@@ -32,7 +32,6 @@
     default=False,
     help="Use a slower SB3 wrapper but keep all the extra training info.",
 )
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -113,7 +112,6 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg, agent_cfg: dict):
     # note: certain randomizations occur in the environment initialization so we set the seed here
     env_cfg.seed = agent_cfg["seed"]
     env_cfg.sim.device = args_cli.device if args_cli.device is not None else env_cfg.sim.device
-    env_cfg.sim.enable_newton_rendering = args_cli.newton_visualizer
 
     # directory for logging into
     run_info = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")

scripts/reinforcement_learning/skrl/play.py

@@ -46,7 +46,6 @@
     help="The RL algorithm used for training the skrl agent.",
 )
 parser.add_argument("--real-time", action="store_true", default=False, help="Run in real-time, if possible.")
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -112,11 +111,7 @@ def main():
 
     # parse configuration
     env_cfg = parse_env_cfg(
-        args_cli.task,
-        device=args_cli.device,
-        num_envs=args_cli.num_envs,
-        use_fabric=not args_cli.disable_fabric,
-        newton_visualizer=args_cli.newton_visualizer,
+        args_cli.task, device=args_cli.device, num_envs=args_cli.num_envs, use_fabric=not args_cli.disable_fabric
     )
     try:
         experiment_cfg = load_cfg_from_registry(task_name, f"skrl_{algorithm}_cfg_entry_point")

scripts/reinforcement_learning/skrl/train.py

@@ -44,7 +44,6 @@
     choices=["AMP", "PPO", "IPPO", "MAPPO"],
     help="The RL algorithm used for training the skrl agent.",
 )
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -113,7 +112,6 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg, agent_cfg: dict):
     # override configurations with non-hydra CLI arguments
     env_cfg.scene.num_envs = args_cli.num_envs if args_cli.num_envs is not None else env_cfg.scene.num_envs
     env_cfg.sim.device = args_cli.device if args_cli.device is not None else env_cfg.sim.device
-    env_cfg.sim.enable_newton_rendering = args_cli.newton_visualizer
 
     # multi-gpu training config
     if args_cli.distributed:

scripts/sim2sim_transfer/rsl_rl_transfer.py

@@ -29,7 +29,6 @@
     help="Use the pre-trained checkpoint from Nucleus.",
 )
 parser.add_argument("--real-time", action="store_true", default=False, help="Run in real-time, if possible.")
-parser.add_argument("--newton_visualizer", action="store_true", default=False, help="Enable Newton rendering.")
 # Joint ordering arguments
 parser.add_argument(
     "--policy_transfer_file",
@@ -147,8 +146,8 @@ def main():
         device=args_cli.device,
         num_envs=args_cli.num_envs,
         use_fabric=not args_cli.disable_fabric,
-        newton_visualizer=args_cli.newton_visualizer,
     )
+
     agent_cfg: RslRlOnPolicyRunnerCfg = cli_args.parse_rsl_rl_cfg(task_name, args_cli)
 
     # specify directory for logging experiments

source/isaaclab/isaaclab/envs/ui/base_env_window.py

@@ -66,6 +66,9 @@ def __init__(self, env: ManagerBasedEnv, window_name: str = "IsaacLab"):
         # Listeners for environment selection changes
         self._ui_listeners: list[ManagerLiveVisualizer] = []
 
+        # Check if any visualizer has live plots enabled
+        self._enable_live_plots = self._check_live_plots_enabled()
+
         print("Creating window for environment.")
         # create window for UI
         self.ui_window = omni.ui.Window(
@@ -102,6 +105,29 @@ def __del__(self):
             self.ui_window.destroy()
             self.ui_window = None
 
+    """
+    Helper methods.
+    """
+
+    def _check_live_plots_enabled(self) -> bool:
+        """Check if any visualizer has live plots enabled.
+
+        Returns:
+            True if any visualizer supports and has live plots enabled, False otherwise.
+        """
+        # Check if simulation has visualizers
+        if not hasattr(self.env.sim, "_visualizers"):
+            return False
+
+        # Check each visualizer
+        for visualizer in self.env.sim._visualizers:
+            # Check if visualizer supports live plots and has it enabled
+            if hasattr(visualizer, "cfg") and hasattr(visualizer.cfg, "enable_live_plots"):
+                if visualizer.supports_live_plots() and visualizer.cfg.enable_live_plots:
+                    return True
+
+        return False
+
     """
     Build sub-sections of the UI.
     """
@@ -421,6 +447,11 @@ def _create_debug_vis_ui_element(self, name: str, elem: object):
                 is_checked = (hasattr(elem.cfg, "debug_vis") and elem.cfg.debug_vis) or (
                     hasattr(elem, "debug_vis") and elem.debug_vis
                 )
+
+            # Auto-enable live plots for ManagerLiveVisualizer if visualizer has enable_live_plots=True
+            if isinstance(elem, ManagerLiveVisualizer) and self._enable_live_plots:
+                is_checked = True
+
             self.ui_window_elements[f"{name}_cb"] = SimpleCheckBox(
                 model=omni.ui.SimpleBoolModel(),
                 enabled=elem.has_debug_vis_implementation,
@@ -435,6 +466,9 @@ def _create_debug_vis_ui_element(self, name: str, elem: object):
             if not elem.set_vis_frame(self.ui_window_elements[f"{name}_panel"]):
                 print(f"Frame failed to set for ManagerLiveVisualizer: {name}")
 
+            # Pass the enable_live_plots flag to the visualizer
+            elem._auto_expand_frames = self._enable_live_plots
+
         # Add listener for environment selection changes
         if isinstance(elem, ManagerLiveVisualizer):
             self._ui_listeners.append(elem)