TF9 Saving and Restoring -1.ipynb

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   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "import tensorflow as tf"
   ]
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   "cell_type": "code",
   "execution_count": 2,
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   "source": [
    "a = tf.get_variable(\"a\", shape=[5], initializer=tf.zeros_initializer)\n",
    "b = tf.get_variable(\"b\", shape=[5], initializer=tf.zeros_initializer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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       "tensorflow.python.ops.variables.Variable"
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   "source": [
    "in_a = a.assign(a+1)\n",
    "in_b = b.assign(b+2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
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     "data": {
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       "tensorflow.python.framework.ops.Tensor"
      ]
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     "metadata": {},
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  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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   "source": [
    "init = tf.global_variables_initializer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Saves all variables so that they can be restored later\n",
    "saver = tf.train.Saver()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "with tf.Session() as sess:\n",
    "    sess.run(init)\n",
    "    in_a.op.run()\n",
    "    in_b.op.run()\n",
    "    saver.save(sess, 'D:/model-info.ckpt')\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "collapsed": true
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