PrimAITE/src/primaite/notebooks/training_example_sb3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from primaite.game.game import PrimaiteGame\n",
    "from primaite.game.environment import PrimaiteGymEnv\n",
    "import yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from primaite.config.load import example_config_path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "installing DNSServer on node domain_controller\n",
      "installing DatabaseClient on node web_server\n",
      "installing WebServer on node web_server\n",
      "installing DatabaseService on node database_server\n",
      "service type not found DatabaseBackup\n",
      "installing DataManipulationBot on node client_1\n",
      "installing DNSClient on node client_1\n",
      "installing DNSClient on node client_2\n"
     ]
    }
   ],
   "source": [
    "with open(example_config_path(), 'r') as f:\n",
    "    cfg = yaml.safe_load(f)\n",
    "\n",
    "game = PrimaiteGame.from_config(cfg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "gym = PrimaiteGymEnv(game=game, agents=game.rl_agents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from stable_baselines3 import PPO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = PPO('MlpPolicy', gym)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<stable_baselines3.ppo.ppo.PPO at 0x7f75352526e0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.learn(total_timesteps=1000)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(\"deleteme\")"
   ]
  }
 ],
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