rl_test.ipynb

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      "\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
      "\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
      "\u001b[1;31mClick <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. \n",
      "\u001b[1;31mView Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
     ]
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   "source": [
    "import os\n",
    "import gymnasium as gym\n",
    "from stable_baselines3 import DQN\n",
    "\n",
    "env = gym.make(\"CartPole-v1\", render_mode=\"human\")"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {},
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     "text": [
      "Using cuda device\n",
      "Wrapping the env with a `Monitor` wrapper\n",
      "Wrapping the env in a DummyVecEnv.\n"
     ]
    }
   ],
   "source": [
    "model = DQN(\"MlpPolicy\", env, verbose=1)\n",
    "model.learn(total_timesteps=10, log_interval=4)\n",
    "model.save(\"dqn_cartpole\")\n",
    "\n",
    "del model # remove to demonstrate saving and loading\n",
    "\n",
    "model = DQN.load(\"dqn_cartpole\")\n",
    "\n",
    "obs, info = env.reset()\n",
    "while True:\n",
    "    action, _states = model.predict(obs, deterministic=True)\n",
    "    obs, reward, terminated, truncated, info = env.step(action)\n",
    "    if terminated or truncated:\n",
    "        obs, info = env.reset()"
   ]
  }
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