Use np.random.set_seed(42) and tf.set_random_seed(42) to make noteboo…

…k's output constant, and simplify code in notebook 15
Sanju-Xaviar · Jun 7, 2017 · 9938d06 · 9938d06
1 parent 6689c3a
commit 9938d06
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diff --git a/12_distributed_tensorflow.ipynb b/12_distributed_tensorflow.ipynb
@@ -55,11 +55,13 @@
     "\n",
     "# Common imports\n",
     "import numpy as np\n",
-    "import numpy.random as rnd\n",
     "import os\n",
     "\n",
     "# to make this notebook's output stable across runs\n",
-    "rnd.seed(42)\n",
+    "def reset_graph(seed=42):\n",
+    "    tf.reset_default_graph()\n",
+    "    tf.set_random_seed(seed)\n",
+    "    np.random.seed(seed)\n",
     "\n",
     "# To plot pretty figures\n",
     "%matplotlib inline\n",
@@ -209,7 +211,7 @@
    },
    "outputs": [],
    "source": [
-    "tf.reset_default_graph()\n",
+    "reset_graph()\n",
     "\n",
     "with tf.device(\"/job:ps\"):\n",
     "    a = tf.Variable(1.0, name=\"a\")\n",
@@ -254,7 +256,7 @@
    },
    "outputs": [],
    "source": [
-    "tf.reset_default_graph()\n",
+    "reset_graph()\n",
     "\n",
     "with tf.device(tf.train.replica_device_setter(\n",
     "        ps_tasks=2,\n",
@@ -300,15 +302,15 @@
      "output_type": "stream",
      "text": [
       "No more files to read\n",
-      "[array([[   4.        ,    5.        ],\n",
-      "       [   1.        , -508.17480469]], dtype=float32), array([1, 0], dtype=int32)]\n",
+      "[array([[  4.00000000e+00,   5.00000000e+00],\n",
+      "       [  1.00000000e+00,   8.62997533e-19]], dtype=float32), array([1, 0], dtype=int32)]\n",
       "[array([[ 7.,  8.]], dtype=float32), array([0], dtype=int32)]\n",
       "No more training instances\n"
      ]
     }
    ],
    "source": [
-    "tf.reset_default_graph()\n",
+    "reset_graph()\n",
     "\n",
     "test_csv = open(\"my_test.csv\", \"w\")\n",
     "test_csv.write(\"x1, x2 , target\\n\")\n",
@@ -393,15 +395,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[array([[   1.        , -508.17480469],\n",
-      "       [   7.        ,    8.        ]], dtype=float32), array([0, 0], dtype=int32)]\n",
-      "[array([[ 4.,  5.]], dtype=float32), array([1], dtype=int32)]\n",
+      "[array([[ 7.,  8.],\n",
+      "       [ 4.,  5.]], dtype=float32), array([0, 1], dtype=int32)]\n",
+      "[array([[  1.00000000e+00,   8.62997533e-19]], dtype=float32), array([0], dtype=int32)]\n",
       "No more training instances\n"
      ]
     }
    ],
    "source": [
-    "tf.reset_default_graph()\n",
+    "reset_graph()\n",
     "\n",
     "filename_queue = tf.FIFOQueue(capacity=10, dtypes=[tf.string], shapes=[()])\n",
     "filename = tf.placeholder(tf.string)\n",
@@ -451,15 +453,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[array([[   1.        , -508.17480469],\n",
-      "       [   4.        ,    5.        ]], dtype=float32), array([0, 1], dtype=int32)]\n",
+      "[array([[  4.00000000e+00,   5.00000000e+00],\n",
+      "       [  1.00000000e+00,   8.62997533e-19]], dtype=float32), array([1, 0], dtype=int32)]\n",
       "[array([[ 7.,  8.]], dtype=float32), array([0], dtype=int32)]\n",
       "No more training instances\n"
      ]
     }
    ],
    "source": [
-    "tf.reset_default_graph()\n",
+    "reset_graph()\n",
     "\n",
     "def read_and_push_instance(filename_queue, instance_queue):\n",
     "    reader = tf.TextLineReader(skip_header_lines=1)\n",
@@ -529,7 +531,7 @@
     }
    ],
    "source": [
-    "tf.reset_default_graph()\n",
+    "reset_graph()\n",
     "\n",
     "q = tf.FIFOQueue(capacity=10, dtypes=[tf.float32], shapes=[()])\n",
     "v = tf.placeholder(tf.float32)\n",
@@ -577,7 +579,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true,
     "deletable": true,