code-02-VariableFunctions.ipynb

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    "import numpy as np\n",
    "import tensorflow as tf\n",
    "\n",
    "\n",
    "def weight_variable(shape):\n",
    "  \"\"\"Generates a weight variable of a given shape.\"\"\"\n",
    "  initial = tf.truncated_normal(shape, stddev=0.1)\n",
    "  return tf.Variable(initial)\n",
    "\n",
    "\n",
    "def bias_variable(shape):\n",
    "  \"\"\"Generates a bias variable of a given shape.\"\"\"\n",
    "  initial = tf.constant(0.1, shape=shape)\n",
    "  return tf.Variable(initial)\n",
    "\n",
    "\n",
    "old_v = tf.logging.get_verbosity()\n",
    "tf.logging.set_verbosity(tf.logging.ERROR)\n",
    "\n",
    "from tensorflow.examples.tutorials.mnist import input_data\n",
    "def main():\n",
    "    mnist = input_data.read_data_sets(\"MNIST_data/\", one_hot=True)\n",
    "    train_data = mnist.train.images  # Return np.array\n",
    "    train_labels = np.asarray(mnist.train.labels, dtype=np.int32)\n",
    "    eval_data = mnist.test.images  # Return np.array\n",
    "    eval_labels = np.asarray(mnist.test.labels, dtype=np.int32)\n",
    "    \n",
    "    # Placeholder that will be fed image data.\n",
    "    x = tf.placeholder(tf.float32, [None, 784])\n",
    "    # Placeholder that will be fed the correct labels.\n",
    "    y_ = tf.placeholder(tf.float32, [None, 10])\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    main()\n",
    "tf.logging.set_verbosity(old_v)"
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