From e05d4b36acb1f3e7f45991d507c5c94d20b5b30a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= <ageron@users.noreply.github.com>
Date: Tue, 8 May 2018 19:40:05 +0200
Subject: [PATCH] tf.contrib.layers.variance_scaling_initializer moved to
 tf.variance_scaling_initializer

---
 16_reinforcement_learning.ipynb | 19 +++++--------------
 1 file changed, 5 insertions(+), 14 deletions(-)

diff --git a/16_reinforcement_learning.ipynb b/16_reinforcement_learning.ipynb
index 30f2ab2..67ce80d 100644
--- a/16_reinforcement_learning.ipynb
+++ b/16_reinforcement_learning.ipynb
@@ -574,15 +574,6 @@
     "    plt.show()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "openai_cart_pole_rendering = False  # don't try, just use the safe way?"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 26,
@@ -783,7 +774,7 @@
     "n_inputs = 4  # == env.observation_space.shape[0]\n",
     "n_hidden = 4  # it's a simple task, we don't need more than this\n",
     "n_outputs = 1 # only outputs the probability of accelerating left\n",
-    "initializer = tf.contrib.layers.variance_scaling_initializer()\n",
+    "initializer = tf.variance_scaling_initializer()\n",
     "\n",
     "# 2. Build the neural network\n",
     "X = tf.placeholder(tf.float32, shape=[None, n_inputs])\n",
@@ -883,7 +874,7 @@
     "\n",
     "learning_rate = 0.01\n",
     "\n",
-    "initializer = tf.contrib.layers.variance_scaling_initializer()\n",
+    "initializer = tf.variance_scaling_initializer()\n",
     "\n",
     "X = tf.placeholder(tf.float32, shape=[None, n_inputs])\n",
     "y = tf.placeholder(tf.float32, shape=[None, n_outputs])\n",
@@ -1008,7 +999,7 @@
     "\n",
     "learning_rate = 0.01\n",
     "\n",
-    "initializer = tf.contrib.layers.variance_scaling_initializer()\n",
+    "initializer = tf.variance_scaling_initializer()\n",
     "\n",
     "X = tf.placeholder(tf.float32, shape=[None, n_inputs])\n",
     "\n",
@@ -1481,7 +1472,7 @@
     "n_hidden = 512\n",
     "hidden_activation = tf.nn.relu\n",
     "n_outputs = env.action_space.n  # 9 discrete actions are available\n",
-    "initializer = tf.contrib.layers.variance_scaling_initializer()\n",
+    "initializer = tf.variance_scaling_initializer()\n",
     "\n",
     "def q_network(X_state, name):\n",
     "    prev_layer = X_state / 128.0 # scale pixel intensities to the [-1.0, 1.0] range.\n",
@@ -1924,7 +1915,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.5.2"
   },
   "nav_menu": {},
   "toc": {