莫凡 Placeholder 传入值.ipynb

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   "source": [
    "https://morvanzhou.github.io/tutorials/machine-learning/tensorflow/2-5-placeholde/\n",
    "\n",
    "这一次我们会讲到 Tensorflow 中的 placeholder , placeholder 是 Tensorflow 中的占位符，暂时储存变量.\n",
    "\n",
    "\n",
    "Tensorflow 如果想要从外部传入data, 那就需要用到 `tf.placeholder()`, 然后以这种形式传输数据 `sess.run(***, feed_dict={input: **})`."
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     "text": [
      "input1的内容是: Tensor(\"Placeholder:0\", dtype=float32)\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "## #在 Tensorflow 中需要定义 placeholder 的 type ，一般为 float32 形式\n",
    "input1 = tf.placeholder(tf.float32)\n",
    "input2 = tf.placeholder(tf.float32)\n",
    "print(\"input1的内容是:\",input1)\n",
    "\n",
    "# mul = multiply 是将input1和input2 做乘法运算，并输出为 output \n",
    "ouput = tf.multiply(input1, input2)"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "接下来, 传值的工作交给了` sess.run()` , 需要传入的值放在了`feed_dict={}` 并一一对应每一个` input. placeholder 与 feed_dict={} 是绑定在一起出现的。\n",
    "**feed_dict_dict={}字典的形式**"
   ]
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   "cell_type": "code",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 12.]\n"
     ]
    }
   ],
   "source": [
    "with tf.Session() as sess:\n",
    "    print(sess.run(ouput, feed_dict={input1: [6.], input2: [2.]}))"
   ]
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