Chapter14.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "n_inputs = 3\n",
    "n_neurons = 5\n",
    "\n",
    "X0 = tf.placeholder(tf.float32, [None, n_inputs])\n",
    "X1 = tf.placeholder(tf.float32, [None, n_inputs])\n",
    "\n",
    "Wx = tf.Variable(tf.random_normal(shape=[n_inputs, n_neurons], dtype=tf.float32))\n",
    "Wy = tf.Variable(tf.random_normal(shape=[n_neurons, n_neurons], dtype=tf.float32))\n",
    "b = tf.Variable(tf.zeros([1, n_neurons], dtype=tf.float32))\n",
    "\n",
    "Y0 = tf.tanh(tf.matmul(X0, Wx) + b)\n",
    "Y1 = tf.tanh(tf.matmul(Y0, Wy) + tf.matmul(X1, Wx) + b)\n",
    "\n",
    "init = tf.global_variables_initializer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Mini-batch:        instance 0,instance 1,instance 2,instance 3\n",
    "X0_batch = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 0, 1]]) # t = 0\n",
    "X1_batch = np.array([[9, 8, 7], [0, 0, 0], [6, 5, 4], [3, 2, 1]]) # t = 1\n",
    "\n",
    "with tf.Session() as sess:\n",
    "    init.run()\n",
    "    Y0_val, Y1_val = sess.run([Y0, Y1], feed_dict={X0: X0_batch, X1: X1_batch})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.9896037   0.98322809  0.9423064  -0.98603791 -0.85516715]\n",
      " [-0.99999934  1.          0.99999911 -0.99991047 -0.99996161]\n",
      " [-1.          1.          1.         -0.99999952 -1.        ]\n",
      " [-0.13124153  1.         -0.97877198 -0.45485467 -0.99732679]]\n",
      "[[-1.          1.          1.         -0.99877924 -1.        ]\n",
      " [-0.98797798  0.22817647  0.99582082  0.89101845  0.44615522]\n",
      " [-1.          1.          1.         -0.81775808 -0.99999607]\n",
      " [-0.99872553  0.99999696  0.99969614  0.04345548 -0.71792346]]\n"
     ]
    }
   ],
   "source": [
    "print(Y0_val)\n",
    "print(Y1_val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X0 = tf.placeholder(tf.float32, [None, n_inputs])\n",
    "X1 = tf.placeholder(tf.float32, [None, n_inputs])\n",
    "\n",
    "basic_cell = tf.contrib.rnn.BasicRNNCell(num_units=n_neurons)\n",
    "output_seqs, states = tf.contrib.rnn.static_rnn(\n",
    "                          basic_cell, [X0, X1], dtype=tf.float32)\n",
    "Y0, Y1 = output_seqs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Variable rnn/basic_rnn_cell/kernel already exists, disallowed. Did you mean to set reuse=True or reuse=tf.AUTO_REUSE in VarScope? Originally defined at:\n\n  File \"<ipython-input-4-5f9ffbe566e6>\", line 6, in <module>\n    basic_cell, [X0, X1], dtype=tf.float32)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2862, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2802, in run_ast_nodes\n    if self.run_code(code, result):\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-7ea11065d805>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mbasic_cell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBasicRNNCell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnum_units\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mn_neurons\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m output_seqs, states = tf.contrib.rnn.static_rnn(\n\u001b[0;32m----> 7\u001b[0;31m                           basic_cell, X_seqs, dtype=tf.float32)\n\u001b[0m\u001b[1;32m      8\u001b[0m \u001b[0moutputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtranspose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstack\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput_seqs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mperm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py\u001b[0m in \u001b[0;36mstatic_rnn\u001b[0;34m(cell, inputs, initial_state, dtype, sequence_length, scope)\u001b[0m\n\u001b[1;32m   1251\u001b[0m             state_size=cell.state_size)\n\u001b[1;32m   1252\u001b[0m       \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1253\u001b[0;31m         \u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcall_cell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1254\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1255\u001b[0m       \u001b[0moutputs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m()\u001b[0m\n\u001b[1;32m   1238\u001b[0m         \u001b[0mvarscope\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreuse_variables\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1239\u001b[0m       \u001b[0;31m# pylint: disable=cell-var-from-loop\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1240\u001b[0;31m       \u001b[0mcall_cell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1241\u001b[0m       \u001b[0;31m# pylint: enable=cell-var-from-loop\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1242\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0msequence_length\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs, state, scope)\u001b[0m\n\u001b[1;32m    181\u001b[0m       with vs.variable_scope(vs.get_variable_scope(),\n\u001b[1;32m    182\u001b[0m                              custom_getter=self._rnn_get_variable):\n\u001b[0;32m--> 183\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mRNNCell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    185\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_rnn_get_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgetter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/layers/base.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    538\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0min_graph_mode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    539\u001b[0m           \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_assert_input_compatibility\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 540\u001b[0;31m         \u001b[0moutputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    541\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    542\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0moutputs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36mcall\u001b[0;34m(self, inputs, state)\u001b[0m\n\u001b[1;32m    259\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    260\u001b[0m     \u001b[0;34m\"\"\"Most basic RNN: output = new_state = act(W * input + U * state + B).\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 261\u001b[0;31m     \u001b[0moutput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_activation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_linear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_num_units\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    262\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    263\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36m_linear\u001b[0;34m(args, output_size, bias, bias_initializer, kernel_initializer)\u001b[0m\n\u001b[1;32m   1128\u001b[0m         \u001b[0m_WEIGHTS_VARIABLE_NAME\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mtotal_arg_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput_size\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1129\u001b[0m         \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1130\u001b[0;31m         initializer=kernel_initializer)\n\u001b[0m\u001b[1;32m   1131\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1132\u001b[0m       \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmath_ops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatmul\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweights\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36mget_variable\u001b[0;34m(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter, constraint)\u001b[0m\n\u001b[1;32m   1193\u001b[0m       \u001b[0mpartitioner\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpartitioner\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1194\u001b[0m       \u001b[0muse_resource\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_resource\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcustom_getter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcustom_getter\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1195\u001b[0;31m       constraint=constraint)\n\u001b[0m\u001b[1;32m   1196\u001b[0m get_variable_or_local_docstring = (\n\u001b[1;32m   1197\u001b[0m     \"\"\"%s\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36mget_variable\u001b[0;34m(self, var_store, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter, constraint)\u001b[0m\n\u001b[1;32m   1082\u001b[0m           \u001b[0mpartitioner\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpartitioner\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1083\u001b[0m           \u001b[0muse_resource\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_resource\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcustom_getter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcustom_getter\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1084\u001b[0;31m           constraint=constraint)\n\u001b[0m\u001b[1;32m   1085\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1086\u001b[0m   def _get_partitioned_variable(self,\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36mget_variable\u001b[0;34m(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter, constraint)\u001b[0m\n\u001b[1;32m    415\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;34m\"constraint\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mestimator_util\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfn_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcustom_getter\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    416\u001b[0m         \u001b[0mcustom_getter_kwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"constraint\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstraint\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 417\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mcustom_getter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mcustom_getter_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    418\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    419\u001b[0m       return _true_getter(\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36m_rnn_get_variable\u001b[0;34m(self, getter, *args, **kwargs)\u001b[0m\n\u001b[1;32m    184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    185\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_rnn_get_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgetter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 186\u001b[0;31m     \u001b[0mvariable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    187\u001b[0m     trainable = (variable in tf_variables.trainable_variables() or\n\u001b[1;32m    188\u001b[0m                  (isinstance(variable, tf_variables.PartitionedVariable) and\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36m_true_getter\u001b[0;34m(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, constraint)\u001b[0m\n\u001b[1;32m    392\u001b[0m           \u001b[0mtrainable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrainable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcollections\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcollections\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    393\u001b[0m           \u001b[0mcaching_device\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcaching_device\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 394\u001b[0;31m           use_resource=use_resource, constraint=constraint)\n\u001b[0m\u001b[1;32m    395\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    396\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcustom_getter\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36m_get_single_variable\u001b[0;34m(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape, use_resource, constraint)\u001b[0m\n\u001b[1;32m    732\u001b[0m                          \u001b[0;34m\"reuse=tf.AUTO_REUSE in VarScope? \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    733\u001b[0m                          \"Originally defined at:\\n\\n%s\" % (\n\u001b[0;32m--> 734\u001b[0;31m                              name, \"\".join(traceback.format_list(tb))))\n\u001b[0m\u001b[1;32m    735\u001b[0m       \u001b[0mfound_var\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_vars\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    736\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mshape\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_compatible_with\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfound_var\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Variable rnn/basic_rnn_cell/kernel already exists, disallowed. Did you mean to set reuse=True or reuse=tf.AUTO_REUSE in VarScope? Originally defined at:\n\n  File \"<ipython-input-4-5f9ffbe566e6>\", line 6, in <module>\n    basic_cell, [X0, X1], dtype=tf.float32)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2862, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2802, in run_ast_nodes\n    if self.run_code(code, result):\n"
     ]
    }
   ],
   "source": [
    "n_steps = 2\n",
    "\n",
    "X = tf.placeholder(tf.float32, [None, n_steps, n_inputs])\n",
    "X_seqs = tf.unstack(tf.transpose(X, perm=[1, 0, 2]))\n",
    "basic_cell = tf.contrib.rnn.BasicRNNCell(num_units=n_neurons)\n",
    "output_seqs, states = tf.contrib.rnn.static_rnn(\n",
    "                          basic_cell, X_seqs, dtype=tf.float32)\n",
    "outputs = tf.transpose(tf.stack(output_seqs), perm=[1, 0, 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'outputs' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-7-e7f92a6fb111>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSession\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msess\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m     \u001b[0minit\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     \u001b[0moutputs_val\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0moutputs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeed_dict\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mX_batch\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'outputs' is not defined"
     ]
    }
   ],
   "source": [
    "X_batch = np.array([\n",
    "         # t = 0     t = 1\n",
    "        [[0, 1, 2], [9, 8, 7]], # instance 0\n",
    "        [[3, 4, 5], [0, 0, 0]], # instance 1\n",
    "        [[6, 7, 8], [6, 5, 4]], # instance 2\n",
    "        [[9, 0, 1], [3, 2, 1]], # instance 3\n",
    "    ])\n",
    "\n",
    "with tf.Session() as sess:\n",
    "    init.run()\n",
    "    outputs_val = outputs.eval(feed_dict={X: X_batch})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Variable rnn/basic_rnn_cell/kernel already exists, disallowed. Did you mean to set reuse=True or reuse=tf.AUTO_REUSE in VarScope? Originally defined at:\n\n  File \"<ipython-input-4-5f9ffbe566e6>\", line 6, in <module>\n    basic_cell, [X0, X1], dtype=tf.float32)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2862, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2802, in run_ast_nodes\n    if self.run_code(code, result):\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-e0649bee9c8a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0mbasic_cell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontrib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBasicRNNCell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnum_units\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mn_neurons\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0moutputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstates\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdynamic_rnn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbasic_cell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloat32\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0mlogits\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfully_connected\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstates\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn_outputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mactivation_fn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py\u001b[0m in \u001b[0;36mdynamic_rnn\u001b[0;34m(cell, inputs, sequence_length, initial_state, dtype, parallel_iterations, swap_memory, time_major, scope)\u001b[0m\n\u001b[1;32m    612\u001b[0m         \u001b[0mswap_memory\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mswap_memory\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    613\u001b[0m         \u001b[0msequence_length\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msequence_length\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 614\u001b[0;31m         dtype=dtype)\n\u001b[0m\u001b[1;32m    615\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    616\u001b[0m     \u001b[0;31m# Outputs of _dynamic_rnn_loop are always shaped [time, batch, depth].\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py\u001b[0m in \u001b[0;36m_dynamic_rnn_loop\u001b[0;34m(cell, inputs, initial_state, parallel_iterations, swap_memory, sequence_length, dtype)\u001b[0m\n\u001b[1;32m    775\u001b[0m       \u001b[0mloop_vars\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput_ta\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    776\u001b[0m       \u001b[0mparallel_iterations\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mparallel_iterations\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 777\u001b[0;31m       swap_memory=swap_memory)\n\u001b[0m\u001b[1;32m    778\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    779\u001b[0m   \u001b[0;31m# Unpack final output if not using output tuples.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py\u001b[0m in \u001b[0;36mwhile_loop\u001b[0;34m(cond, body, loop_vars, shape_invariants, parallel_iterations, back_prop, swap_memory, name)\u001b[0m\n\u001b[1;32m   2795\u001b[0m     \u001b[0mloop_context\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mWhileContext\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparallel_iterations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mback_prop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mswap_memory\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# pylint: disable=redefined-outer-name\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2796\u001b[0m     \u001b[0mops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_to_collection\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mGraphKeys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mWHILE_CONTEXT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mloop_context\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2797\u001b[0;31m     \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mloop_context\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mBuildLoop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcond\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mloop_vars\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshape_invariants\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2798\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2799\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py\u001b[0m in \u001b[0;36mBuildLoop\u001b[0;34m(self, pred, body, loop_vars, shape_invariants)\u001b[0m\n\u001b[1;32m   2619\u001b[0m       \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mEnter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2620\u001b[0m       original_body_result, exit_vars = self._BuildLoop(\n\u001b[0;32m-> 2621\u001b[0;31m           pred, body, original_loop_vars, loop_vars, shape_invariants)\n\u001b[0m\u001b[1;32m   2622\u001b[0m     \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2623\u001b[0m       \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mExit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/control_flow_ops.py\u001b[0m in \u001b[0;36m_BuildLoop\u001b[0;34m(self, pred, body, original_loop_vars, loop_vars, shape_invariants)\u001b[0m\n\u001b[1;32m   2569\u001b[0m         \u001b[0mstructure\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moriginal_loop_vars\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2570\u001b[0m         flat_sequence=vars_for_body_with_tensor_arrays)\n\u001b[0;32m-> 2571\u001b[0;31m     \u001b[0mbody_result\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbody\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mpacked_vars_for_body\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2572\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mnest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_sequence\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbody_result\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2573\u001b[0m       \u001b[0mbody_result\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mbody_result\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py\u001b[0m in \u001b[0;36m_time_step\u001b[0;34m(time, output_ta_t, state)\u001b[0m\n\u001b[1;32m    760\u001b[0m           skip_conditionals=True)\n\u001b[1;32m    761\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 762\u001b[0;31m       \u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnew_state\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcall_cell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    763\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    764\u001b[0m     \u001b[0;31m# Pack state if using state tuples\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m()\u001b[0m\n\u001b[1;32m    746\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    747\u001b[0m     \u001b[0minput_t\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnest\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpack_sequence_as\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstructure\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflat_sequence\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minput_t\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 748\u001b[0;31m     \u001b[0mcall_cell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mlambda\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_t\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    749\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    750\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0msequence_length\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs, state, scope)\u001b[0m\n\u001b[1;32m    181\u001b[0m       with vs.variable_scope(vs.get_variable_scope(),\n\u001b[1;32m    182\u001b[0m                              custom_getter=self._rnn_get_variable):\n\u001b[0;32m--> 183\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mRNNCell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    185\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_rnn_get_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgetter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/layers/base.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, inputs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    538\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0min_graph_mode\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    539\u001b[0m           \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_assert_input_compatibility\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 540\u001b[0;31m         \u001b[0moutputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    541\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    542\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0moutputs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36mcall\u001b[0;34m(self, inputs, state)\u001b[0m\n\u001b[1;32m    259\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mcall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    260\u001b[0m     \u001b[0;34m\"\"\"Most basic RNN: output = new_state = act(W * input + U * state + B).\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 261\u001b[0;31m     \u001b[0moutput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_activation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_linear\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_num_units\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    262\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    263\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36m_linear\u001b[0;34m(args, output_size, bias, bias_initializer, kernel_initializer)\u001b[0m\n\u001b[1;32m   1128\u001b[0m         \u001b[0m_WEIGHTS_VARIABLE_NAME\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mtotal_arg_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput_size\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1129\u001b[0m         \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1130\u001b[0;31m         initializer=kernel_initializer)\n\u001b[0m\u001b[1;32m   1131\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1132\u001b[0m       \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmath_ops\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmatmul\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mweights\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36mget_variable\u001b[0;34m(name, shape, dtype, initializer, regularizer, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter, constraint)\u001b[0m\n\u001b[1;32m   1193\u001b[0m       \u001b[0mpartitioner\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpartitioner\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1194\u001b[0m       \u001b[0muse_resource\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_resource\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcustom_getter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcustom_getter\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1195\u001b[0;31m       constraint=constraint)\n\u001b[0m\u001b[1;32m   1196\u001b[0m get_variable_or_local_docstring = (\n\u001b[1;32m   1197\u001b[0m     \"\"\"%s\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36mget_variable\u001b[0;34m(self, var_store, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter, constraint)\u001b[0m\n\u001b[1;32m   1082\u001b[0m           \u001b[0mpartitioner\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpartitioner\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1083\u001b[0m           \u001b[0muse_resource\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0muse_resource\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcustom_getter\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcustom_getter\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1084\u001b[0;31m           constraint=constraint)\n\u001b[0m\u001b[1;32m   1085\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1086\u001b[0m   def _get_partitioned_variable(self,\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36mget_variable\u001b[0;34m(self, name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, custom_getter, constraint)\u001b[0m\n\u001b[1;32m    415\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;34m\"constraint\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mestimator_util\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfn_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcustom_getter\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    416\u001b[0m         \u001b[0mcustom_getter_kwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"constraint\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstraint\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 417\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mcustom_getter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mcustom_getter_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    418\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    419\u001b[0m       return _true_getter(\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/rnn_cell_impl.py\u001b[0m in \u001b[0;36m_rnn_get_variable\u001b[0;34m(self, getter, *args, **kwargs)\u001b[0m\n\u001b[1;32m    184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    185\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_rnn_get_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgetter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 186\u001b[0;31m     \u001b[0mvariable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    187\u001b[0m     trainable = (variable in tf_variables.trainable_variables() or\n\u001b[1;32m    188\u001b[0m                  (isinstance(variable, tf_variables.PartitionedVariable) and\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36m_true_getter\u001b[0;34m(name, shape, dtype, initializer, regularizer, reuse, trainable, collections, caching_device, partitioner, validate_shape, use_resource, constraint)\u001b[0m\n\u001b[1;32m    392\u001b[0m           \u001b[0mtrainable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrainable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcollections\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcollections\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    393\u001b[0m           \u001b[0mcaching_device\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcaching_device\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidate_shape\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate_shape\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 394\u001b[0;31m           use_resource=use_resource, constraint=constraint)\n\u001b[0m\u001b[1;32m    395\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    396\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcustom_getter\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/tensorflow/python/ops/variable_scope.py\u001b[0m in \u001b[0;36m_get_single_variable\u001b[0;34m(self, name, shape, dtype, initializer, regularizer, partition_info, reuse, trainable, collections, caching_device, validate_shape, use_resource, constraint)\u001b[0m\n\u001b[1;32m    732\u001b[0m                          \u001b[0;34m\"reuse=tf.AUTO_REUSE in VarScope? \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    733\u001b[0m                          \"Originally defined at:\\n\\n%s\" % (\n\u001b[0;32m--> 734\u001b[0;31m                              name, \"\".join(traceback.format_list(tb))))\n\u001b[0m\u001b[1;32m    735\u001b[0m       \u001b[0mfound_var\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_vars\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    736\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mshape\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_compatible_with\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfound_var\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_shape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Variable rnn/basic_rnn_cell/kernel already exists, disallowed. Did you mean to set reuse=True or reuse=tf.AUTO_REUSE in VarScope? Originally defined at:\n\n  File \"<ipython-input-4-5f9ffbe566e6>\", line 6, in <module>\n    basic_cell, [X0, X1], dtype=tf.float32)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2862, in run_code\n    exec(code_obj, self.user_global_ns, self.user_ns)\n  File \"/home/santiago/.pyenv/versions/3.6.2/envs/handson/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2802, in run_ast_nodes\n    if self.run_code(code, result):\n"
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