{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.simplefilter(action='ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 创建计算图并执行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "area: 48\n"
     ]
    }
   ],
   "source": [
    "width = tf.placeholder('int32', name='width')\n",
    "height = tf.placeholder('int32', name='height')\n",
    "area = tf.multiply(width, height, name='area')\n",
    "\n",
    "with tf.Session() as sess:\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "    print('area:', sess.run(area, feed_dict={width: 6, height: 8}))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 将计算图写入log文件, 用于在 TensorBoard 中查看"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf.summary.merge_all()  # 将所有要显示在 TensorBoard 的数据整合\n",
    "train_writer = tf.summary.FileWriter('log/graph_area', sess.graph)"
   ]
  }
 ],
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