01.01test1.ipynb

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      "权重： <tf.Variable 'Variable:0' shape=(1,) dtype=float32_ref>\n"
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    "### tensorflow版本：V1.3 ,V 0.12\n",
    "\n",
    "\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "\n",
    "## create data      astype()\n",
    "x_data = np.random.rand(100).astype(np.float32)\n",
    "y_data = x_data*0.1 + 0.3\n",
    "\n",
    "### create tensorflow structure start\n",
    "Weights = tf.Variable(tf.random_uniform([1], -1.0, 1.0)) # 随机变量生成的数列,-1到1\n",
    "print(\"权重：\",Weights)\n",
    "biases =  tf.Variable(tf.zeros([1]))\n",
    "\n",
    "y = Weights*x_data + biases\n",
    "\n",
    "\n",
    "loss = tf.reduce_mean(tf.square(y-y_data))\n",
    "# 优化\n",
    "optimizer = tf.train.GradientDescentOptimizer(0.5)\n",
    "# 此方法Use `tf.global_variables_initializer` instead.\n",
    "# train = tf.initialize_all_variables()\n",
    "# train = tf.global_variables_initializer()\n",
    "train = optimizer.minimize(loss)\n",
    "\n",
    "\n",
    "# init = tf.initialize_all_variables()      Use `tf.global_variables_initializer` instead.\n",
    "init = tf.global_variables_initializer() "
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      "0 [-0.13183489] [ 0.61876029]\n",
      "20 [ 0.02479587] [ 0.34222719]\n",
      "40 [ 0.08189277] [ 0.31016722]\n",
      "60 [ 0.09564024] [ 0.302448]\n",
      "80 [ 0.09895033] [ 0.30058941]\n",
      "100 [ 0.09974729] [ 0.3001419]\n",
      "120 [ 0.09993916] [ 0.30003417]\n",
      "140 [ 0.09998536] [ 0.30000824]\n",
      "160 [ 0.09999649] [ 0.30000198]\n",
      "180 [ 0.09999917] [ 0.30000049]\n",
      "200 [ 0.09999979] [ 0.30000013]\n"
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   "source": [
    "## create tensorflow structure end\n",
    "\n",
    "# sess = tf.Session()\n",
    "# sess.run(init)  # Very important 激活\n",
    "\n",
    "# for step in range(201):\n",
    "#     sess.run(train)\n",
    "#     if step%20 ==0:\n",
    "#         print(step, sess.run(Weights), sess.run(biases))\n",
    "\n",
    "# sess = tf.Session()\n",
    "with tf.Session() as sess:\n",
    "    sess.run(init)  # Very important 激活\n",
    "    for step in range(201):\n",
    "        sess.run(train)\n",
    "        if step%20 ==0:\n",
    "            print(step, sess.run(Weights), sess.run(biases))\n"
   ]
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