[wip] Add initial design for Visualizers

scripts/environments/random_agent.py

@@ -18,7 +18,12 @@
 )
 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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -52,8 +57,22 @@ 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,
     )
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
     # create environment
     env = gym.make(args_cli.task, cfg=env_cfg)
 

scripts/environments/zero_agent.py

@@ -18,7 +18,12 @@
 )
 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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -52,8 +57,22 @@ 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,
     )
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
     # create environment
     env = gym.make(args_cli.task, cfg=env_cfg)
 

scripts/reinforcement_learning/rl_games/play.py

@@ -32,7 +32,12 @@
     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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -84,8 +89,22 @@ 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,
     )
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
     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 +38,12 @@
     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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -90,7 +95,21 @@ 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
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
 
     # randomly sample a seed if seed = -1
     if args_cli.seed == -1:

scripts/reinforcement_learning/rsl_rl/play.py

@@ -34,7 +34,12 @@
     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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append RSL-RL cli arguments
 cli_args.add_rsl_rl_args(parser)
 # append AppLauncher cli args
@@ -96,7 +101,21 @@ 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
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
 
     # specify directory for logging experiments
     log_root_path = os.path.join("logs", "rsl_rl", agent_cfg.experiment_name)
@@ -117,11 +136,15 @@ 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
+    # Set play mode for visualizers
+    if env_cfg.sim.visualizers is not None:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if isinstance(env_cfg.sim.visualizers, list):
+            for viz_cfg in env_cfg.sim.visualizers:
+                viz_cfg.train_mode = False
+        elif isinstance(env_cfg.sim.visualizers, NewtonVisualizerCfg):
+            env_cfg.sim.visualizers.train_mode = False
         else:
             # Create newton_cfg if it doesn't exist
             from isaaclab.sim._impl.newton_manager_cfg import NewtonCfg

scripts/reinforcement_learning/rsl_rl/train.py

@@ -32,7 +32,12 @@
     "--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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append RSL-RL cli arguments
 cli_args.add_rsl_rl_args(parser)
 # append AppLauncher cli args
@@ -119,7 +124,21 @@ 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
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
 
     # multi-gpu training configuration
     if args_cli.distributed:

scripts/reinforcement_learning/sb3/play.py

@@ -39,7 +39,12 @@
     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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -87,8 +92,22 @@ 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,
     )
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
 
     task_name = args_cli.task.split(":")[-1]
     train_task_name = task_name.replace("-Play", "")

scripts/reinforcement_learning/sb3/train.py

@@ -32,7 +32,12 @@
     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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
@@ -113,7 +118,21 @@ 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
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
 
     # directory for logging into
     run_info = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")

scripts/reinforcement_learning/skrl/play.py

@@ -46,7 +46,12 @@
     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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -116,8 +121,22 @@ 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,
     )
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
     try:
         experiment_cfg = load_cfg_from_registry(task_name, f"skrl_{algorithm}_cfg_entry_point")
     except ValueError:

scripts/reinforcement_learning/skrl/train.py

@@ -44,7 +44,12 @@
     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.")
+parser.add_argument(
+    "--visualize",
+    action="store_true",
+    default=False,
+    help="Launch visualizer(s). Uses visualizers defined in environment config, or defaults to Newton OpenGL if none configured.",
+)
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
@@ -113,7 +118,21 @@ 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
+
+    # handle visualizer launch
+    if args_cli.visualize:
+        from isaaclab.sim.visualizers import NewtonVisualizerCfg
+
+        if env_cfg.sim.visualizers is None:
+            # No visualizers in config - use default Newton visualizer
+            env_cfg.sim.visualizers = NewtonVisualizerCfg(enabled=True)
+        else:
+            # Enable configured visualizer(s)
+            if isinstance(env_cfg.sim.visualizers, list):
+                for viz_cfg in env_cfg.sim.visualizers:
+                    viz_cfg.enabled = True
+            else:
+                env_cfg.sim.visualizers.enabled = True
 
     # multi-gpu training config
     if args_cli.distributed: