DQN_from_git.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"DQN_from_git.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"code","metadata":{"id":"XP8ykUFLzk8o","colab_type":"code","outputId":"61ad28a3-9419-4d5f-e838-d3a053daa693","executionInfo":{"status":"ok","timestamp":1591440918920,"user_tz":-180,"elapsed":73846,"user":{"displayName":"Brian Loco","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhUZKRJwpWk51WQ9tBJhrtqtjdRRL_mVu05rggMl6E=s64","userId":"01102478983375575371"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["#add \" > /dev/null 2>&1\" at the end of each command to ignore output\n","!pip install gym pyvirtualdisplay\n","!apt-get install -y xvfb python-opengl ffmpeg\n","###\n","!apt-get update\n","!pip install --upgrade setuptools\n","!pip install \"gym[atari]\"==0.9.5\n","!pip install opencv-python\n","!pip install torch\n","!pip install matplotlib\n","!pip install --force \"gym[atari]\"==0.9.5"],"execution_count":4,"outputs":[{"output_type":"stream","text":["Requirement already satisfied: gym in /usr/local/lib/python3.6/dist-packages (0.17.2)\n","Collecting pyvirtualdisplay\n","  Downloading https://files.pythonhosted.org/packages/d0/8a/643043cc70791367bee2d19eb20e00ed1a246ac48e5dbe57bbbcc8be40a9/PyVirtualDisplay-1.3.2-py2.py3-none-any.whl\n","Requirement already satisfied: pyglet<=1.5.0,>=1.4.0 in /usr/local/lib/python3.6/dist-packages (from gym) (1.5.0)\n","Requirement already satisfied: numpy>=1.10.4 in /usr/local/lib/python3.6/dist-packages (from gym) (1.18.4)\n","Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from gym) (1.4.1)\n","Requirement already satisfied: cloudpickle<1.4.0,>=1.2.0 in /usr/local/lib/python3.6/dist-packages (from gym) (1.3.0)\n","Collecting EasyProcess\n","  Downloading https://files.pythonhosted.org/packages/48/3c/75573613641c90c6d094059ac28adb748560d99bd27ee6f80cce398f404e/EasyProcess-0.3-py2.py3-none-any.whl\n","Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from pyglet<=1.5.0,>=1.4.0->gym) (0.16.0)\n","Installing collected packages: EasyProcess, pyvirtualdisplay\n","Successfully installed EasyProcess-0.3 pyvirtualdisplay-1.3.2\n","Reading package lists... Done\n","Building dependency tree       \n","Reading state information... Done\n","ffmpeg is already the newest version (7:3.4.6-0ubuntu0.18.04.1).\n","Suggested packages:\n","  libgle3\n","The following NEW packages will be installed:\n","  python-opengl xvfb\n","0 upgraded, 2 newly installed, 0 to remove and 32 not upgraded.\n","Need to get 1,280 kB of archives.\n","After this operation, 7,682 kB of additional disk space will be used.\n","Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 python-opengl all 3.1.0+dfsg-1 [496 kB]\n","Get:2 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 xvfb amd64 2:1.19.6-1ubuntu4.4 [784 kB]\n","Fetched 1,280 kB in 1s (922 kB/s)\n","Selecting previously unselected package python-opengl.\n","(Reading database ... 144467 files and directories currently installed.)\n","Preparing to unpack .../python-opengl_3.1.0+dfsg-1_all.deb ...\n","Unpacking python-opengl (3.1.0+dfsg-1) ...\n","Selecting previously unselected package xvfb.\n","Preparing to unpack .../xvfb_2%3a1.19.6-1ubuntu4.4_amd64.deb ...\n","Unpacking xvfb (2:1.19.6-1ubuntu4.4) ...\n","Setting up python-opengl (3.1.0+dfsg-1) ...\n","Setting up xvfb (2:1.19.6-1ubuntu4.4) ...\n","Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n","Get:1 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran35/ InRelease [3,626 B]\n","Ign:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease\n","Ign:3 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  InRelease\n","Get:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release [697 B]\n","Get:5 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]\n","Hit:6 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Release\n","Get:7 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Release.gpg [836 B]\n","Get:8 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease [21.3 kB]\n","Hit:9 http://archive.ubuntu.com/ubuntu bionic InRelease\n","Get:11 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]\n","Get:12 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic InRelease [15.4 kB]\n","Ign:13 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Packages\n","Get:13 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  Packages [162 kB]\n","Get:14 http://security.ubuntu.com/ubuntu bionic-security/main amd64 Packages [933 kB]\n","Get:15 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB]\n","Get:16 http://security.ubuntu.com/ubuntu bionic-security/universe amd64 Packages [856 kB]\n","Get:17 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic/main amd64 Packages [37.4 kB]\n","Get:18 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 Packages [1,230 kB]\n","Get:19 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic/main Sources [1,830 kB]\n","Get:20 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 Packages [1,387 kB]\n","Get:21 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic/main amd64 Packages [882 kB]\n","Fetched 7,612 kB in 4s (1,787 kB/s)\n","Reading package lists... 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folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\u001b[0m\n","\u001b[31mERROR: albumentations 0.1.12 has requirement imgaug<0.2.7,>=0.2.5, but you'll have imgaug 0.2.9 which is incompatible.\u001b[0m\n","\u001b[?25hInstalling collected packages: chardet, urllib3, certifi, idna, requests, numpy, six, pyglet, PyOpenGL, atari-py, Pillow, gym\n","  Found existing installation: chardet 3.0.4\n","    Uninstalling chardet-3.0.4:\n","      Successfully uninstalled chardet-3.0.4\n","  Found existing installation: urllib3 1.24.3\n","    Uninstalling urllib3-1.24.3:\n","      Successfully uninstalled urllib3-1.24.3\n","  Found existing installation: certifi 2020.4.5.1\n","    Uninstalling certifi-2020.4.5.1:\n","      Successfully uninstalled certifi-2020.4.5.1\n","  Found existing installation: idna 2.9\n","    Uninstalling idna-2.9:\n","      Successfully uninstalled idna-2.9\n","  Found existing installation: requests 2.23.0\n","    Uninstalling requests-2.23.0:\n","      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PyOpenGL-3.1.5 atari-py-0.2.6 certifi-2020.4.5.1 chardet-3.0.4 gym-0.9.5 idna-2.9 numpy-1.18.5 pyglet-1.5.5 requests-2.23.0 six-1.15.0 urllib3-1.25.9\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.colab-display-data+json":{"pip_warning":{"packages":["PIL","certifi","chardet","idna","numpy","requests","six","urllib3"]}}},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"vGWT7Yrhz2_E","colab_type":"code","outputId":"55b7f854-3185-4bbb-d8c7-f8a5180a59f6","executionInfo":{"status":"ok","timestamp":1591440982908,"user_tz":-180,"elapsed":3081,"user":{"displayName":"Brian Loco","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhUZKRJwpWk51WQ9tBJhrtqtjdRRL_mVu05rggMl6E=s64","userId":"01102478983375575371"}},"colab":{"base_uri":"https://localhost:8080/","height":131}},"source":["import gym\n","print(gym.__version__)  # make sure it says 0.9.5\n","from gym import logger as gymlogger\n","from gym import wrappers\n","import tensorflow as tf\n","import torch\n","import numpy as np\n","import random\n","import matplotlib\n","import matplotlib.pyplot as plt\n","%matplotlib inline\n","import math\n","import glob\n","import io\n","import base64\n","from IPython.display import HTML\n","\n","from IPython import display as ipythondisplay\n","######\n","from pyvirtualdisplay import Display\n","display = Display(visible=0, size=(1400, 900))\n","display.start()\n","# Get Atari games.\n","benchmark = gym.benchmark_spec('Atari40M')\n","task = benchmark.tasks[3]\n","env = gym.make(task.env_id)\n","\n","env = gym.make('PongNoFrameskip-v4')  # this command should succeeds\n","print(env)\n","print(gym.__version__)"],"execution_count":1,"outputs":[{"output_type":"stream","text":["0.9.5\n"],"name":"stdout"},{"output_type":"stream","text":["[2020-06-06 10:56:22,140] Making new env: PongNoFrameskip-v4\n","/usr/local/lib/python3.6/dist-packages/gym/envs/registration.py:17: PkgResourcesDeprecationWarning: Parameters to load are deprecated.  Call .resolve and .require separately.\n","  result = entry_point.load(False)\n","[2020-06-06 10:56:22,369] Making new env: PongNoFrameskip-v4\n"],"name":"stderr"},{"output_type":"stream","text":["<TimeLimit<AtariEnv<PongNoFrameskip-v4>>>\n","0.9.5\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"8ghJwUCbObss","colab_type":"code","outputId":"a955a04e-e2c8-4570-bc44-ad2495809b10","executionInfo":{"status":"ok","timestamp":1591441050578,"user_tz":-180,"elapsed":759,"user":{"displayName":"Brian Loco","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhUZKRJwpWk51WQ9tBJhrtqtjdRRL_mVu05rggMl6E=s64","userId":"01102478983375575371"}},"colab":{"base_uri":"https://localhost:8080/","height":70}},"source":["%cd /content/drive/My Drive/Colab Notebooks/Reinforcement_Project"],"execution_count":7,"outputs":[{"output_type":"stream","text":["[Errno 2] No such file or directory: '/content/drive/My Drive/Colab Notebooks/Reinforcement_Project'\n","/content\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"bdkHQeZLkzLP","colab_type":"code","outputId":"efaa8681-1ba3-4d24-85f4-94b7139a1cc8","executionInfo":{"status":"ok","timestamp":1591441048187,"user_tz":-180,"elapsed":750,"user":{"displayName":"Brian Loco","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhUZKRJwpWk51WQ9tBJhrtqtjdRRL_mVu05rggMl6E=s64","userId":"01102478983375575371"}},"colab":{"base_uri":"https://localhost:8080/","height":53}},"source":["from google.colab import drive\n","drive.mount('/content/drive')"],"execution_count":6,"outputs":[{"output_type":"stream","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"AHpNuWSI_9J2","colab_type":"text"},"source":["# New Section"]},{"cell_type":"code","metadata":{"id":"ReYBw_ZdToNt","colab_type":"code","outputId":"f8cc9ce3-2bf2-476c-b515-f63988f1d4e6","executionInfo":{"status":"ok","timestamp":1591202710359,"user_tz":-180,"elapsed":229091,"user":{"displayName":"Brian Loco","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhUZKRJwpWk51WQ9tBJhrtqtjdRRL_mVu05rggMl6E=s64","userId":"01102478983375575371"}},"colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["!python main_from_git.py"],"execution_count":0,"outputs":[{"output_type":"stream","text":["[2020-06-06 11:34:53,121] Making new env: PongNoFrameskip-v4\n","/usr/local/lib/python3.6/dist-packages/gym/envs/registration.py:17: PkgResourcesDeprecationWarning: Parameters to load are deprecated.  Call .resolve and .require separately.\n","  result = entry_point.load(False)\n","[2020-06-06 11:34:53,590] Clearing 18 monitor files from previous run (because force=True was provided)\n","[2020-06-06 11:34:56,771] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000000.mp4\n","tcmalloc: large alloc 7056007168 bytes == 0x7fe3b96de000 @  0x7fe5f33d01e7 0x7fe5f0ef65e1 0x7fe5f0f5ac78 0x7fe5f0f5af37 0x7fe5f0ff2f28 0x50a635 0x50cd96 0x509758 0x50a48d 0x50bfb4 0x507d64 0x509a90 0x50a48d 0x50cd96 0x507d64 0x509a90 0x50a48d 0x50bfb4 0x507d64 0x50ae13 0x634c82 0x634d37 0x6384ef 0x639091 0x4b0d00 0x7fe5f2fcdb97 0x5b250a\n","[2020-06-06 11:35:01,654] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000001.mp4\n","[2020-06-06 11:35:17,603] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000008.mp4\n","[2020-06-06 11:35:57,057] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000027.mp4\n","/content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/dqn_learn_from_git.py:117: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n","  return model(Variable(obs, volatile=True)).data.max(1)[1].view(1,1)\n","[2020-06-06 11:37:27,273] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000064.mp4\n","/content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/dqn_learn_from_git.py:117: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n","  return model(Variable(obs, volatile=True)).data.max(1)[1].view(1,1)\n","Timestep 60000\n","mean reward (100 episodes) -20.265625\n","best mean reward -inf\n","episodes 64\n","exploration 0.946000\n","Saved to statistics_from_git.pkl\n","Timestep 70000\n","mean reward (100 episodes) -20.226667\n","best mean reward -inf\n","episodes 75\n","exploration 0.937000\n","Saved to statistics_from_git.pkl\n","Timestep 80000\n","mean reward (100 episodes) -20.267442\n","best mean reward -inf\n","episodes 86\n","exploration 0.928000\n","Saved to statistics_from_git.pkl\n","Timestep 90000\n","mean reward (100 episodes) -20.268041\n","best mean reward -inf\n","episodes 97\n","exploration 0.919000\n","Saved to statistics_from_git.pkl\n","Timestep 100000\n","mean reward (100 episodes) -20.250000\n","best mean reward -20.230000\n","episodes 108\n","exploration 0.910000\n","Saved to statistics_from_git.pkl\n","Timestep 110000\n","mean reward (100 episodes) -20.230000\n","best mean reward -20.220000\n","episodes 118\n","exploration 0.901000\n","Saved to statistics_from_git.pkl\n","[2020-06-06 11:41:21,977] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000125.mp4\n","/content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/dqn_learn_from_git.py:117: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n","  return model(Variable(obs, volatile=True)).data.max(1)[1].view(1,1)\n","Timestep 120000\n","mean reward (100 episodes) -20.290000\n","best mean reward -20.220000\n","episodes 130\n","exploration 0.892000\n","Saved to statistics_from_git.pkl\n","Timestep 130000\n","mean reward (100 episodes) -20.280000\n","best mean reward -20.220000\n","episodes 141\n","exploration 0.883000\n","Saved to statistics_from_git.pkl\n","Timestep 140000\n","mean reward (100 episodes) -20.320000\n","best mean reward -20.220000\n","episodes 153\n","exploration 0.874000\n","Saved to statistics_from_git.pkl\n","Timestep 150000\n","mean reward (100 episodes) -20.360000\n","best mean reward -20.220000\n","episodes 164\n","exploration 0.865000\n","Saved to statistics_from_git.pkl\n","Timestep 160000\n","mean reward (100 episodes) -20.370000\n","best mean reward -20.220000\n","episodes 175\n","exploration 0.856000\n","Saved to statistics_from_git.pkl\n","Timestep 170000\n","mean reward (100 episodes) -20.380000\n","best mean reward -20.220000\n","episodes 187\n","exploration 0.847000\n","Saved to statistics_from_git.pkl\n","Timestep 180000\n","mean reward (100 episodes) -20.420000\n","best mean reward -20.220000\n","episodes 198\n","exploration 0.838000\n","Saved to statistics_from_git.pkl\n","Timestep 190000\n","mean reward (100 episodes) -20.410000\n","best mean reward -20.220000\n","episodes 209\n","exploration 0.829000\n","Saved to statistics_from_git.pkl\n","[2020-06-06 11:47:05,603] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000216.mp4\n","/content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/dqn_learn_from_git.py:117: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n","  return model(Variable(obs, volatile=True)).data.max(1)[1].view(1,1)\n","Timestep 200000\n","mean reward (100 episodes) -20.450000\n","best mean reward -20.220000\n","episodes 221\n","exploration 0.820000\n","Saved to statistics_from_git.pkl\n","Timestep 210000\n","mean reward (100 episodes) -20.360000\n","best mean reward -20.220000\n","episodes 231\n","exploration 0.811000\n","Saved to statistics_from_git.pkl\n","Timestep 220000\n","mean reward (100 episodes) -20.350000\n","best mean reward -20.220000\n","episodes 242\n","exploration 0.802000\n","Saved to statistics_from_git.pkl\n","Timestep 230000\n","mean reward (100 episodes) -20.320000\n","best mean reward -20.220000\n","episodes 254\n","exploration 0.793000\n","Saved to statistics_from_git.pkl\n","Timestep 240000\n","mean reward (100 episodes) -20.340000\n","best mean reward -20.220000\n","episodes 265\n","exploration 0.784000\n","Saved to statistics_from_git.pkl\n","Timestep 250000\n","mean reward (100 episodes) -20.350000\n","best mean reward -20.220000\n","episodes 275\n","exploration 0.775000\n","Saved to statistics_from_git.pkl\n","Timestep 260000\n","mean reward (100 episodes) -20.300000\n","best mean reward -20.220000\n","episodes 287\n","exploration 0.766000\n","Saved to statistics_from_git.pkl\n","Timestep 270000\n","mean reward (100 episodes) -20.300000\n","best mean reward -20.220000\n","episodes 298\n","exploration 0.757000\n","Saved to statistics_from_git.pkl\n","Timestep 280000\n","mean reward (100 episodes) -20.360000\n","best mean reward -20.220000\n","episodes 309\n","exploration 0.748000\n","Saved to statistics_from_git.pkl\n","Timestep 290000\n","mean reward (100 episodes) -20.330000\n","best mean reward -20.220000\n","episodes 320\n","exploration 0.739000\n","Saved to statistics_from_git.pkl\n","Timestep 300000\n","mean reward (100 episodes) -20.380000\n","best mean reward -20.220000\n","episodes 331\n","exploration 0.730000\n","Saved to statistics_from_git.pkl\n","[2020-06-06 11:55:27,775] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000343.mp4\n","/content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/dqn_learn_from_git.py:117: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n","  return model(Variable(obs, volatile=True)).data.max(1)[1].view(1,1)\n","Timestep 310000\n","mean reward (100 episodes) -20.380000\n","best mean reward -20.220000\n","episodes 343\n","exploration 0.721000\n","Saved to statistics_from_git.pkl\n","Timestep 320000\n","mean reward (100 episodes) -20.360000\n","best mean reward -20.220000\n","episodes 354\n","exploration 0.712000\n","Saved to statistics_from_git.pkl\n","Timestep 330000\n","mean reward (100 episodes) -20.300000\n","best mean reward -20.220000\n","episodes 365\n","exploration 0.703000\n","Saved to statistics_from_git.pkl\n","Timestep 340000\n","mean reward (100 episodes) -20.310000\n","best mean reward -20.220000\n","episodes 376\n","exploration 0.694000\n","Saved to statistics_from_git.pkl\n","Timestep 350000\n","mean reward (100 episodes) -20.320000\n","best mean reward -20.220000\n","episodes 387\n","exploration 0.685000\n","Saved to statistics_from_git.pkl\n","Timestep 360000\n","mean reward (100 episodes) -20.290000\n","best mean reward -20.220000\n","episodes 398\n","exploration 0.676000\n","Saved to statistics_from_git.pkl\n","Timestep 370000\n","mean reward (100 episodes) -20.310000\n","best mean reward -20.220000\n","episodes 410\n","exploration 0.667000\n","Saved to statistics_from_git.pkl\n","Timestep 380000\n","mean reward (100 episodes) -20.310000\n","best mean reward -20.220000\n","episodes 421\n","exploration 0.658000\n","Saved to statistics_from_git.pkl\n","Timestep 390000\n","mean reward (100 episodes) -20.350000\n","best mean reward -20.220000\n","episodes 432\n","exploration 0.649000\n","Saved to statistics_from_git.pkl\n","Timestep 400000\n","mean reward (100 episodes) -20.320000\n","best mean reward -20.220000\n","episodes 443\n","exploration 0.640000\n","Saved to statistics_from_git.pkl\n","Timestep 410000\n","mean reward (100 episodes) -20.390000\n","best mean reward -20.220000\n","episodes 455\n","exploration 0.631000\n","Saved to statistics_from_git.pkl\n","Timestep 420000\n","mean reward (100 episodes) -20.450000\n","best mean reward -20.220000\n","episodes 466\n","exploration 0.622000\n","Saved to statistics_from_git.pkl\n","Timestep 430000\n","mean reward (100 episodes) -20.440000\n","best mean reward -20.220000\n","episodes 477\n","exploration 0.613000\n","Saved to statistics_from_git.pkl\n","Timestep 440000\n","mean reward (100 episodes) -20.510000\n","best mean reward -20.220000\n","episodes 488\n","exploration 0.604000\n","Saved to statistics_from_git.pkl\n","Timestep 450000\n","mean reward (100 episodes) -20.520000\n","best mean reward -20.220000\n","episodes 500\n","exploration 0.595000\n","Saved to statistics_from_git.pkl\n","Timestep 460000\n","mean reward (100 episodes) -20.480000\n","best mean reward -20.220000\n","episodes 511\n","exploration 0.586000\n","Saved to statistics_from_git.pkl\n","[2020-06-06 12:06:43,578] Starting new video recorder writing to /content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/tmp/gym-results/openaigym.video.0.2291.video000512.mp4\n","/content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project/dqn_learn_from_git.py:117: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.\n","  return model(Variable(obs, volatile=True)).data.max(1)[1].view(1,1)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"NUzTamK3czwh","colab_type":"code","outputId":"61c58354-3198-476d-f0ab-c6ee30a16440","executionInfo":{"status":"ok","timestamp":1591441058036,"user_tz":-180,"elapsed":575,"user":{"displayName":"Brian Loco","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhUZKRJwpWk51WQ9tBJhrtqtjdRRL_mVu05rggMl6E=s64","userId":"01102478983375575371"}},"colab":{"base_uri":"https://localhost:8080/","height":53}},"source":["# from google.colab import drive\n","# drive.mount('/content/drive')\n","%cd /content/drive/My Drive/Reinforcement_Project"],"execution_count":8,"outputs":[{"output_type":"stream","text":["/content/drive/.shortcut-targets-by-id/1-X_-J3Lsyt883funEKPzSKBsf0KXf3Sd/Reinforcement_Project\n"],"name":"stdout"}]}]}