The example of train-T1

rl_game/demo/train.py

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+import sys
+import os
+# 关键：确保当前目录在 sys.path 中，这样才能直接 from config 导入
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+import argparse
+from isaaclab.app import AppLauncher
+
+# 添加启动参数
+parser = argparse.ArgumentParser(description="Train T1 robot with rl_games.")
+parser.add_argument("--num_envs", type=int, default=16384, help="Number of envs to run.")
+AppLauncher.add_app_launcher_args(parser)
+args_cli = parser.parse_args()
+
+# 启动仿真器
+app_launcher = AppLauncher(args_cli)
+simulation_app = app_launcher.app
+
+import torch
+import gymnasium as gym
+from isaaclab_rl.rl_games import RlGamesVecEnvWrapper
+from rl_games.torch_runner import Runner
+import yaml
+from config.t1_env_cfg import T1EnvCfg
+from rl_games.common import env_configurations, vecenv
+
+gym.register(
+    id="Isaac-T1-Walking-v0",
+    entry_point="isaaclab.envs:ManagerBasedRLEnv", # Isaac Lab 统一的强化学习环境入口
+    kwargs={
+        "cfg": T1EnvCfg(),
+    },
+)
+
+def main():
+    # 1. 创建环境 (保持不变)
+    env = gym.make("Isaac-T1-Walking-v0", num_envs=args_cli.num_envs)
+
+    # 2. 包装环境 (保持不变)
+    wrapped_env = RlGamesVecEnvWrapper(
+        env,
+        rl_device=args_cli.device,
+        clip_obs=5.0,
+        clip_actions=100.0
+    )
+
+    vecenv.register('as_is', lambda config_name, num_actors, **kwargs: wrapped_env)
+
+    # 注册环境配置
+    env_configurations.register('rlgym', {
+        'vecenv_type': 'as_is',
+        'env_creator': lambda **kwargs: wrapped_env
+    })
+
+    # 3. 加载 PPO 配置 (保持不变)
+    config_path = os.path.join(os.path.dirname(__file__), "config", "ppo_cfg.yaml")
+    with open(config_path, "r") as f:
+        rl_config = yaml.safe_load(f)
+
+    # 设置日志路径
+    rl_game_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), "."))
+    log_dir = os.path.join(rl_game_dir, "logs")
+    rl_config['params']['config']['train_dir'] = log_dir
+
+    # 4. 启动训练
+    runner = Runner()
+
+    # 此时 rl_config 只有文本和数字，没有复杂对象，deepcopy 会成功
+    runner.load(rl_config)
+
+    # 在 run 时传入对象是安全的
+    runner.run({
+        "train": True,
+        "play": False,
+        "vec_env": wrapped_env
+    })
+
+    simulation_app.close()
+
+# PYTHONPATH=. python rl_game/your_file_name/train.py
+
+if __name__ == "__main__":
+    main()