Enables hydra for all play.py scripts (#2995)

# Description
This PR enables hydra override for all play.py scripts
I have mannually tested all rl_frameworks and worked.

I remember there is a issue related, but couldn't find it, feel free to
add to it if you found it.

## Type of change

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applicable. -->
- New feature (non-breaking change which adds functionality)

## Screenshots

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## Checklist

- [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with
`./isaaclab.sh --format`
- [ ] 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

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---------
Co-authored-by: Kelly Guo <kellyguo123@hotmail.com>

scripts/reinforcement_learning/rl_games/play.py

@@ -8,6 +8,7 @@
 """Launch Isaac Sim Simulator first."""
 
 import argparse
+import sys
 
 from isaaclab.app import AppLauncher
 
@@ -35,11 +36,13 @@ parser.add_argument("--real-time", action="store_true", default=False, help="Run
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
-args_cli = parser.parse_args()
+args_cli, hydra_args = parser.parse_known_args()
 # always enable cameras to record video
 if args_cli.video:
     args_cli.enable_cameras = True
 
+# clear out sys.argv for Hydra
+sys.argv = [sys.argv[0]] + hydra_args
 # launch omniverse app
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app
@@ -57,7 +60,13 @@ from rl_games.common import env_configurations, vecenv
 from rl_games.common.player import BasePlayer
 from rl_games.torch_runner import Runner
 
-from isaaclab.envs import DirectMARLEnv, multi_agent_to_single_agent
+from isaaclab.envs import (
+    DirectMARLEnv,
+    DirectMARLEnvCfg,
+    DirectRLEnvCfg,
+    ManagerBasedRLEnvCfg,
+    multi_agent_to_single_agent,
+)
 from isaaclab.utils.assets import retrieve_file_path
 from isaaclab.utils.dict import print_dict
 from isaaclab.utils.pretrained_checkpoint import get_published_pretrained_checkpoint
@@ -65,19 +74,19 @@ from isaaclab.utils.pretrained_checkpoint import get_published_pretrained_checkp
 from isaaclab_rl.rl_games import RlGamesGpuEnv, RlGamesVecEnvWrapper
 
 import isaaclab_tasks  # noqa: F401
-from isaaclab_tasks.utils import get_checkpoint_path, load_cfg_from_registry, parse_env_cfg
+from isaaclab_tasks.utils import get_checkpoint_path
+from isaaclab_tasks.utils.hydra import hydra_task_config
 
 # PLACEHOLDER: Extension template (do not remove this comment)
 
 
-def main():
+@hydra_task_config(args_cli.task, "rl_games_cfg_entry_point")
+def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agent_cfg: dict):
     """Play with RL-Games agent."""
     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
-    )
-    agent_cfg = load_cfg_from_registry(args_cli.task, "rl_games_cfg_entry_point")
+    # 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
 
     # specify directory for logging experiments
     log_root_path = os.path.join("logs", "rl_games", agent_cfg["params"]["config"]["name"])

scripts/reinforcement_learning/rsl_rl/play.py

@@ -8,6 +8,7 @@
 """Launch Isaac Sim Simulator first."""
 
 import argparse
+import sys
 
 from isaaclab.app import AppLauncher
 
@@ -33,11 +34,15 @@ parser.add_argument("--real-time", action="store_true", default=False, help="Run
 cli_args.add_rsl_rl_args(parser)
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
-args_cli = parser.parse_args()
+# parse the arguments
+args_cli, hydra_args = parser.parse_known_args()
 # always enable cameras to record video
 if args_cli.video:
     args_cli.enable_cameras = True
 
+# clear out sys.argv for Hydra
+sys.argv = [sys.argv[0]] + hydra_args
+
 # launch omniverse app
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app
@@ -51,7 +56,13 @@ import torch
 
 from rsl_rl.runners import OnPolicyRunner
 
-from isaaclab.envs import DirectMARLEnv, multi_agent_to_single_agent
+from isaaclab.envs import (
+    DirectMARLEnv,
+    DirectMARLEnvCfg,
+    DirectRLEnvCfg,
+    ManagerBasedRLEnvCfg,
+    multi_agent_to_single_agent,
+)
 from isaaclab.utils.assets import retrieve_file_path
 from isaaclab.utils.dict import print_dict
 from isaaclab.utils.pretrained_checkpoint import get_published_pretrained_checkpoint
@@ -59,19 +70,20 @@ from isaaclab.utils.pretrained_checkpoint import get_published_pretrained_checkp
 from isaaclab_rl.rsl_rl import RslRlOnPolicyRunnerCfg, RslRlVecEnvWrapper, export_policy_as_jit, export_policy_as_onnx
 
 import isaaclab_tasks  # noqa: F401
-from isaaclab_tasks.utils import get_checkpoint_path, parse_env_cfg
+from isaaclab_tasks.utils import get_checkpoint_path
+from isaaclab_tasks.utils.hydra import hydra_task_config
 
 # PLACEHOLDER: Extension template (do not remove this comment)
 
 
-def main():
+@hydra_task_config(args_cli.task, "rsl_rl_cfg_entry_point")
+def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agent_cfg: RslRlOnPolicyRunnerCfg):
     """Play with RSL-RL agent."""
     task_name = args_cli.task.split(":")[-1]
-    # 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
-    )
-    agent_cfg: RslRlOnPolicyRunnerCfg = cli_args.parse_rsl_rl_cfg(task_name, args_cli)
+    # override configurations with non-hydra CLI arguments
+    agent_cfg = cli_args.update_rsl_rl_cfg(agent_cfg, args_cli)
+    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
 
     # specify directory for logging experiments
     log_root_path = os.path.join("logs", "rsl_rl", agent_cfg.experiment_name)

scripts/reinforcement_learning/sb3/play.py

@@ -8,6 +8,7 @@
 """Launch Isaac Sim Simulator first."""
 
 import argparse
+import sys
 from pathlib import Path
 
 from isaaclab.app import AppLauncher
@@ -42,11 +43,14 @@ parser.add_argument(
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
 # parse the arguments
-args_cli = parser.parse_args()
+args_cli, hydra_args = parser.parse_known_args()
+
 # always enable cameras to record video
 if args_cli.video:
     args_cli.enable_cameras = True
 
+# clear out sys.argv for Hydra
+sys.argv = [sys.argv[0]] + hydra_args
 # launch omniverse app
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app
@@ -61,25 +65,31 @@ import torch
 from stable_baselines3 import PPO
 from stable_baselines3.common.vec_env import VecNormalize
 
-from isaaclab.envs import DirectMARLEnv, multi_agent_to_single_agent
+from isaaclab.envs import (
+    DirectMARLEnv,
+    DirectMARLEnvCfg,
+    DirectRLEnvCfg,
+    ManagerBasedRLEnvCfg,
+    multi_agent_to_single_agent,
+)
 from isaaclab.utils.dict import print_dict
-from isaaclab.utils.io import load_yaml
 from isaaclab.utils.pretrained_checkpoint import get_published_pretrained_checkpoint
 
 from isaaclab_rl.sb3 import Sb3VecEnvWrapper, process_sb3_cfg
 
 import isaaclab_tasks  # noqa: F401
-from isaaclab_tasks.utils.parse_cfg import get_checkpoint_path, parse_env_cfg
+from isaaclab_tasks.utils.hydra import hydra_task_config
+from isaaclab_tasks.utils.parse_cfg import get_checkpoint_path
 
 # PLACEHOLDER: Extension template (do not remove this comment)
 
 
-def main():
+@hydra_task_config(args_cli.task, "sb3_cfg_entry_point")
+def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agent_cfg: dict):
     """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
-    )
+    # 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
 
     task_name = args_cli.task.split(":")[-1]
     train_task_name = task_name.replace("-Play", "")
@@ -107,8 +117,6 @@ def main():
     # create isaac environment
     env = gym.make(args_cli.task, cfg=env_cfg, render_mode="rgb_array" if args_cli.video else None)
 
-    # load the exact config used for training (instead of the default config)
-    agent_cfg = load_yaml(os.path.join(log_dir, "params", "agent.yaml"))
     # post-process agent configuration
     agent_cfg = process_sb3_cfg(agent_cfg, env.unwrapped.num_envs)
 

scripts/reinforcement_learning/skrl/play.py

@@ -13,6 +13,7 @@ a more user-friendly way.
 """Launch Isaac Sim Simulator first."""
 
 import argparse
+import sys
 
 from isaaclab.app import AppLauncher
 
@@ -49,11 +50,14 @@ parser.add_argument("--real-time", action="store_true", default=False, help="Run
 
 # append AppLauncher cli args
 AppLauncher.add_app_launcher_args(parser)
-args_cli = parser.parse_args()
+# parse the arguments
+args_cli, hydra_args = parser.parse_known_args()
 # always enable cameras to record video
 if args_cli.video:
     args_cli.enable_cameras = True
 
+# clear out sys.argv for Hydra
+sys.argv = [sys.argv[0]] + hydra_args
 # launch omniverse app
 app_launcher = AppLauncher(args_cli)
 simulation_app = app_launcher.app
@@ -82,38 +86,42 @@ if args_cli.ml_framework.startswith("torch"):
 elif args_cli.ml_framework.startswith("jax"):
     from skrl.utils.runner.jax import Runner
 
-from isaaclab.envs import DirectMARLEnv, multi_agent_to_single_agent
+from isaaclab.envs import (
+    DirectMARLEnv,
+    DirectMARLEnvCfg,
+    DirectRLEnvCfg,
+    ManagerBasedRLEnvCfg,
+    multi_agent_to_single_agent,
+)
 from isaaclab.utils.dict import print_dict
 from isaaclab.utils.pretrained_checkpoint import get_published_pretrained_checkpoint
 
 from isaaclab_rl.skrl import SkrlVecEnvWrapper
 
 import isaaclab_tasks  # noqa: F401
-from isaaclab_tasks.utils import get_checkpoint_path, load_cfg_from_registry, parse_env_cfg
+from isaaclab_tasks.utils import get_checkpoint_path
+from isaaclab_tasks.utils.hydra import hydra_task_config
 
 # PLACEHOLDER: Extension template (do not remove this comment)
 
 # config shortcuts
 algorithm = args_cli.algorithm.lower()
+agent_cfg_entry_point = "skrl_cfg_entry_point" if algorithm in ["ppo"] else f"skrl_{algorithm}_cfg_entry_point"
 
 
-def main():
+@hydra_task_config(args_cli.task, agent_cfg_entry_point)
+def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, experiment_cfg: dict):
     """Play with skrl agent."""
+    # 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
+
     # configure the ML framework into the global skrl variable
     if args_cli.ml_framework.startswith("jax"):
         skrl.config.jax.backend = "jax" if args_cli.ml_framework == "jax" else "numpy"
 
     task_name = args_cli.task.split(":")[-1]
 
-    # 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
-    )
-    try:
-        experiment_cfg = load_cfg_from_registry(task_name, f"skrl_{algorithm}_cfg_entry_point")
-    except ValueError:
-        experiment_cfg = load_cfg_from_registry(task_name, "skrl_cfg_entry_point")
-
     # specify directory for logging experiments (load checkpoint)
     log_root_path = os.path.join("logs", "skrl", experiment_cfg["agent"]["experiment"]["directory"])
     log_root_path = os.path.abspath(log_root_path)