main.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "README.md        main.ipynb       \u001B[34msrc\u001B[m\u001B[m\r\n",
      "\u001B[34mdata\u001B[m\u001B[m             requirements.txt \u001B[34mthrash\u001B[m\u001B[m\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:38.435399Z",
     "start_time": "2023-11-27T21:01:38.260610Z"
    }
   },
   "id": "1766a4d0da68f39e"
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "import torch\n",
    "from matplotlib import pyplot as plt\n",
    "from src.rl_algorithm.dqn.DQN_Agent import DQNAgent\n",
    "import gym\n",
    "from collections import deque\n",
    "from gym.wrappers import RecordVideo\n",
    "import src.util as util\n",
    "from src.config import Config"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:41.287888Z",
     "start_time": "2023-11-27T21:01:39.034706Z"
    }
   },
   "id": "204d3b52bf4ca62f"
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ">> Created dir data/rl_class_11-27-2023_22-01-41/models\n",
      ">> Created dir data/rl_class_11-27-2023_22-01-41/plots\n",
      ">> Created dir data/rl_class_11-27-2023_22-01-41/videos\n",
      "Error writing JSON data to data/rl_class_11-27-2023_22-01-41//config.json: Object of type getset_descriptor is not JSON serializable\n",
      ">> Using device: cpu\n"
     ]
    }
   ],
   "source": [
    "# initial setup\n",
    "util.seed_everything()                                # sets all the seeds\n",
    "PATH_ROOT = util.make_all_paths(is_dynamic_root=True) # creates a path for testing \n",
    "util.write_json_to_file(dict(Config.__dict__), file_path=PATH_ROOT+\"/config.json\")  # store the information of simulation\n",
    "\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "print('>> Using device:', device)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:41.301249Z",
     "start_time": "2023-11-27T21:01:41.290047Z"
    }
   },
   "id": "9c61f161267c3f5f"
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "agent = DQNAgent(frames=Config.N_FRAMES, action_space=Config.action_space, device=device, hidden_dimension=Config.HIDDEN_DIMENSION_FC)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:41.584494Z",
     "start_time": "2023-11-27T21:01:41.298624Z"
    }
   },
   "id": "12d2b1571698401e"
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [],
   "source": [
    "# env = gym.make('CarRacing-v2', render_mode=\"human\")  # , render_mode='human')\n",
    "# \n",
    "# # chose each of thw available actions with probability 1/12 \n",
    "# MAX_STEP = 1000\n",
    "# env.reset()\n",
    "# for step in range(MAX_STEP):\n",
    "#     action = agent.act(is_only_random=True)\n",
    "#     next_state, r, epi_done, info, _ = env.step(action)\n",
    "# env.close()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:41.593298Z",
     "start_time": "2023-11-27T21:01:41.586171Z"
    }
   },
   "id": "88b234a315a485e8"
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/matteoprata/opt/anaconda3/envs/rl_course/lib/python3.8/site-packages/gym/wrappers/record_video.py:75: UserWarning: \u001B[33mWARN: Overwriting existing videos at /Users/matteoprata/PycharmProjects/RL23/data/rl_class_11-27-2023_22-01-41/videos folder (try specifying a different `video_folder` for the `RecordVideo` wrapper if this is not desired)\u001B[0m\n",
      "  logger.warn(\n"
     ]
    }
   ],
   "source": [
    "# https://www.gymlibrary.dev/environments/box2d/car_racing/\n",
    "env = gym.make('CarRacing-v2', render_mode=\"rgb_array\")  # , render_mode='human')\n",
    "env = RecordVideo(env, PATH_ROOT + 'videos', episode_trigger=lambda x: x % Config.UPDATE_TARGET_MODEL_FREQUENCY == 0)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:43.249590Z",
     "start_time": "2023-11-27T21:01:43.158065Z"
    }
   },
   "id": "a39ecd4642223cf4"
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [],
   "source": [
    "# episode stats\n",
    "epi_total_rewards = []"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:47.541322Z",
     "start_time": "2023-11-27T21:01:47.537345Z"
    }
   },
   "id": "7bc5d803347d0786"
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "init_state = env.reset()[0]  # 96, 96, 3 pixels image RGB\n",
    "util.plot_frame_car(init_state)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:01:55.380540Z",
     "start_time": "2023-11-27T21:01:55.319618Z"
    }
   },
   "id": "fe375221b52e2674"
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "init_state = util.preprocess_frame_car(init_state)  # 96, 96 pixels image GRAY\n",
    "util.plot_frame_car(init_state)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T21:02:03.548367Z",
     "start_time": "2023-11-27T21:02:03.464996Z"
    }
   },
   "id": "638ae6916220aa56"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}