03-1_Jordan_RNN.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Jordan Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because I could not find any Tensorflow implementation of the Jordan network, I implement the network from scratch, meaning writing codes with tensors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**References**\n",
    "- [How to build a Recurrent Neural Network in TensorFlow (1/7)](https://medium.com/@erikhallstrm/hello-world-rnn-83cd7105b767)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf"
   ]
  },
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   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_value(node):\n",
    "    config = tf.ConfigProto()\n",
    "    config.gpu_options.allow_growth = True\n",
    "    with tf.Session(config=config) as sess:\n",
    "        sess.run(tf.global_variables_initializer())\n",
    "        node_val = sess.run(node)\n",
    "    return node_val\n",
    "        \n",
    "def get_values(node):\n",
    "    config = tf.ConfigProto()\n",
    "    config.gpu_options.allow_growth = True\n",
    "    with tf.Session(config=config) as sess:\n",
    "        sess.run(tf.global_variables_initializer())\n",
    "        nodes_val = sess.run(nodes)\n",
    "    return nodes_val\n",
    "        \n",
    "def get_shape(tensor):\n",
    "    config = tf.ConfigProto()\n",
    "    config.gpu_options.allow_growth = True\n",
    "    with tf.Session(config=config) as sess:\n",
    "        shape_val = sess.run(tf.shape(tensor))\n",
    "    return shape_val "
   ]
  }
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