Merge pull request #316 from yandexdataschool/master-week6-fix-cartpo…

…le-timelimit

[week6] Fix accidental TimeLimit in CartPole

week06_policy_based/reinforce_tensorflow.ipynb

@@ -42,14 +42,13 @@
    "source": [
     "import gym\n",
     "import numpy as np\n",
-    "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
     "%matplotlib inline\n",
     "\n",
     "env = gym.make(\"CartPole-v0\")\n",
     "\n",
     "# gym compatibility: unwrap TimeLimit\n",
-    "if hasattr(env, 'env'):\n",
+    "if hasattr(env, '_max_episode_steps'):\n",
     "    env = env.env\n",
     "\n",
     "env.reset()\n",
@@ -260,7 +259,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def generate_session(t_max=1000):\n",
+    "def generate_session(env, t_max=1000):\n",
     "    \"\"\"play env with REINFORCE agent and train at the session end\"\"\"\n",
     "\n",
     "    # arrays to record session\n",
@@ -302,7 +301,7 @@
     "\n",
     "for i in range(100):\n",
     "\n",
-    "    rewards = [generate_session() for _ in range(100)]  # generate new sessions\n",
+    "    rewards = [generate_session(env) for _ in range(100)]  # generate new sessions\n",
     "\n",
     "    print(\"mean reward:%.3f\" % (np.mean(rewards)))\n",
     "\n",
@@ -326,10 +325,9 @@
    "source": [
     "# record sessions\n",
     "import gym.wrappers\n",
-    "env = gym.wrappers.Monitor(gym.make(\"CartPole-v0\"),\n",
-    "                           directory=\"videos\", force=True)\n",
-    "sessions = [generate_session() for _ in range(100)]\n",
-    "env.close()"
+    "monitor_env = gym.wrappers.Monitor(gym.make(\"CartPole-v0\"), directory=\"videos\", force=True)\n",
+    "sessions = [generate_session(monitor_env) for _ in range(100)]\n",
+    "monitor_env.close()"
    ]
   },
   {