{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5.0, 2.0]\n"
     ]
    }
   ],
   "source": [
    "# Fetch\n",
    "a = tf.constant(1.0)\n",
    "b = tf.constant(2.0)\n",
    "c = tf.constant(3.0)\n",
    "multiply = tf.multiply(a, b)\n",
    "add = tf.add(matmul, c)\n",
    "\n",
    "# Fetch可以运行多个 Op\n",
    "with tf.Session() as sess:\n",
    "    print(sess.run([add, multiply]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 2.]\n"
     ]
    }
   ],
   "source": [
    "# Feed\n",
    "ph1 = tf.placeholder(tf.float32)\n",
    "ph2 = tf.placeholder(tf.float32)\n",
    "m = tf.multiply(ph1, ph2)\n",
    "\n",
    "# 在真正执行的时候，再将数据以字典的形式传入\n",
    "with tf.Session() as sess:\n",
    "    print(sess.run(m, feed_dict={ph1: [1.0], ph2: [2.0]}))"
   ]
  }
 ],
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