The Pessimist Machine.ipynb

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   "source": [
    "# The Pessimistic Machine\n",
    "\n",
    "The Pessimistic is a proof of concept for style adaptation. The machine takes a sentence as input and returns a sentence addressing a similar object but conveying a negative sentiment.\n",
    "\n",
    "The machine needs to be fed with the latent representations of the sentences from the dataset which can be obtained using the script *compute_latent_representations.py*."
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     "text": [
      "Downloading data from data_LMR/..\n",
      "Data already downloaded.\n",
      "Creating Vocabulary..\n",
      "Vocabulary already created.\n",
      "Converting sentences to sequences of ids..\n",
      "Moving some line from test set to train set..\n",
      "latent_dim : 16\n",
      "sequence_max : 30\n",
      "decoder_num_layers : 2\n",
      "beta_period : 500\n",
      "training_dir : logs/no_char2word\n",
      "epoches : 10000\n",
      "batch_size : 600\n",
      "char2word_num_layers : 2\n",
      "initialize : False\n",
      "teacher_forcing : True\n",
      "learning_rate_change_rate : 3000\n",
      "beta_offset : 15\n",
      "encoder_num_layers : 2\n",
      "char2word_state_size : 256\n",
      "sequence_min : 8\n",
      "use_char2word : False\n",
      "dtype_precision : 32\n",
      "cell : GRU\n",
      "use_sentiment_feature : False\n",
      "initial_learning_rate : 0.001\n",
      "decoder_state_size : 1024\n",
      "output_keep_prob : 0.5\n",
      "acceptable_accuracy : 0.4\n",
      "peephole : True\n",
      "input_keep_prob : 0.9\n",
      "encoder_state_size : 1024\n",
      "latent_loss_weight : 0.01\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "import datetime \n",
    "import json\n",
    "from tqdm import tqdm\n",
    "import os\n",
    "import tensorflow as tf\n",
    "import seaborn as sns\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline \n",
    "from bokeh.io import output_notebook\n",
    "from bokeh.plotting import figure, output_file, show, ColumnDataSource\n",
    "from bokeh.models import HoverTool\n",
    "output_notebook()\n",
    "\n",
    "from data_utils_LMR import prepare_data,read_data, EncoderDecoder\n",
    "from model import Vrae as Vrae_model\n",
    "from batch import Generator\n",
    "\n",
    "prepare_data(1000)\n",
    "\n",
    "training_dir = 'logs/'\n",
    "training_dir += 'no_char2word'\n",
    "\n",
    "# sentiment analyzer\n",
    "from nltk.sentiment.vader import SentimentIntensityAnalyzer\n",
    "sentimentAnalyzer = SentimentIntensityAnalyzer()\n",
    "def getSentimentScore(sentence):\n",
    "    scores = sentimentAnalyzer.polarity_scores(sentence)\n",
    "    return (scores['neg'], scores['neu'] ,scores['pos'])\n",
    "\n",
    "class dotdict(dict):\n",
    "    \"\"\"dot.notation access to dictionary attributes\"\"\"\n",
    "    __getattr__ = dict.get\n",
    "    __setattr__ = dict.__setitem__\n",
    "    __delattr__ = dict.__delitem__\n",
    "    \n",
    "def string2bool(st):\n",
    "    if st.lower() == \"true\":\n",
    "        return True\n",
    "    else:\n",
    "        return False\n",
    "    \n",
    "with open(training_dir +'/flags.json', 'r') as fp:\n",
    "    FLAGS = dotdict(json.loads( fp.read() ) )\n",
    "    \n",
    "for k,v in FLAGS.iteritems():\n",
    "    print k,':',v\n",
    "      \n",
    "n_samples = 5000#int(FLAGS.batch_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## k-NN Decoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "77976 points\n"
     ]
    }
   ],
   "source": [
    "labels = []\n",
    "zs = []\n",
    "with tf.gfile.GFile(training_dir + \"/latent_representations.txt\" , mode=\"r\") as source_file:\n",
    "    source = source_file.readline()\n",
    "    counter = 0\n",
    "    while source:\n",
    "        source = source_file.readline()\n",
    "        if len(source.split('|')) > 1:\n",
    "            z_ =  [ float(u) for u in source.split('|')[1].split(',')]\n",
    "            if len(z_) == 16:\n",
    "                labels.append(source.split('|')[0])\n",
    "                zs.append(z_ )\n",
    "            counter += 1\n",
    "print len(zs), 'points'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KDTree\n",
    "kdt = KDTree(np.array(zs), leaf_size=1,metric='euclidean')\n",
    "def getNeighbor(zz, n_similar = 5):\n",
    "    \"\"\" \n",
    "    take a z value and returns the neighrest neighbor in the latent space from the training set\n",
    "    \"\"\"\n",
    "    dist, ind = kdt.query( zz, k=n_similar)\n",
    "    return [ labels[k] for k in list(ind[0]) ], dist"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The VAE model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  reading data line 10000\n",
      "  reading data line 20000\n",
      "  reading data line 30000\n",
      "  reading data line 40000\n",
      "  reading data line 50000\n",
      "  reading data line 60000\n",
      "  reading data line 70000\n",
      "77977  sentences\n"
     ]
    }
   ],
   "source": [
    "with open(training_dir +'/training_parameters.json', 'r') as fp:\n",
    "    training_parameters = json.loads( fp.read() )\n",
    "# vocabulary encoder-decoder\n",
    "encoderDecoder = EncoderDecoder()\n",
    "num_symbols = encoderDecoder.vocabularySize()\n",
    "# prepare data\n",
    "sentences, ratings = read_data( max_size=None, \n",
    "                               max_sentence_size=training_parameters['seq_max'],\n",
    "                               min_sentence_size=int(FLAGS.sequence_min), \n",
    "                               test=False) \n",
    "print len(sentences), \" sentences\"\n",
    "\n",
    "encoderDecoder = EncoderDecoder()\n",
    "\n",
    "config = tf.ConfigProto(\n",
    "        device_count = {'GPU': 0}, # do not use GPU for testing\n",
    "    )\n",
    "\n",
    "FLAGS.peephole = False\n",
    "# load model\n",
    "vrae_model = Vrae_model(char2word_state_size = int(FLAGS.char2word_state_size), \n",
    "                     char2word_num_layers = int(FLAGS.char2word_num_layers), \n",
    "                     encoder_state_size = int(FLAGS.encoder_state_size), \n",
    "                     encoder_num_layers = int(FLAGS.encoder_num_layers), \n",
    "                     decoder_state_size = int(FLAGS.decoder_state_size), \n",
    "                     decoder_num_layers = int(FLAGS.decoder_num_layers), \n",
    "                          latent_dim=int(FLAGS.latent_dim),\n",
    "                         batch_size=n_samples,\n",
    "                         num_symbols=num_symbols,\n",
    "                        latent_loss_weight=float(FLAGS.latent_loss_weight),\n",
    "                         dtype_precision=FLAGS.dtype_precision,\n",
    "                        cell_type=FLAGS.cell, \n",
    "                        peephole=FLAGS.peephole,\n",
    "                        input_keep_prob=float(FLAGS.input_keep_prob),\n",
    "                        output_keep_prob=float(FLAGS.output_keep_prob),\n",
    "                      sentiment_feature = string2bool(FLAGS.use_sentiment_feature),\n",
    "                      use_char2word = string2bool(FLAGS.use_char2word) \n",
    "                       )\n",
    "def zToXdecoded(session,z_sample,s_length):\n",
    "    x_reconstruct = vrae_model.zToX(session,z_sample,s_length)\n",
    "    return encoderDecoder.prettyDecode( np.argmax(x_reconstruct[0], axis= 1) ) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Pessimist Machine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def MachineSays(sess,u,n_sample = 20):\n",
    "    #print train_dir\n",
    "    sent = getSentimentScore(u)\n",
    "    sent_index = 0 # grumpy  \n",
    "    zz = vrae_model.XToz(sess, *encoderDecoder.encodeForTraining(u),sentiment=getSentimentScore(u))[0]\n",
    "    res, dist = getNeighbor( [list(zz)] ,n_sample)\n",
    "    if u.lower() in res:\n",
    "        res.remove(u.lower())\n",
    "    out = []\n",
    "    for uu in sorted(zip(res,list(dist[0])), key=lambda x : getSentimentScore(x[0])[sent_index] , reverse=True):\n",
    "        out.append(uu[0])\n",
    "    return out\n",
    "    #print \"\\n\",dist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from ./logs/no_char2word/model.ckp\n",
      "i hate this movie.\n",
      "i hate this movie.\n",
      "i like this movie.\n",
      "i liked this movies.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i love this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i liked this movie.\n",
      "i like the movie.\n",
      "i like it.\n",
      "i like it.\n",
      "like this one.\n",
      "i love this.\n",
      "i saw this movie on t.\n",
      "i love this movie a lot.\n",
      "i liked those movies.\n"
     ]
    }
   ],
   "source": [
    "answers = []\n",
    "saver = tf.train.Saver()\n",
    "with tf.Session(config=config) as sess:\n",
    "    saver.restore(sess, \"./\"+training_dir+'/model.ckp')\n",
    "    for uu in MachineSays(sess,\"I like this movie.\", 50):\n",
    "        print uu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from ./logs/no_char2word/model.ckp\n"
     ]
    },
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>input</th>\n",
       "      <th>answer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>I totally loved it.</td>\n",
       "      <td>i totally hated the movie.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>I was really bad.</td>\n",
       "      <td>it' s really bad.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>it was terrible.</td>\n",
       "      <td>thats terrible.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>the acting was mostly good.</td>\n",
       "      <td>the acting is mostly horrendously bad.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>I liked this movie.</td>\n",
       "      <td>i liked this movie.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>it was a nice movie.</td>\n",
       "      <td>this is a waste of time and money.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>the story was amazing.</td>\n",
       "      <td>the story was bad.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>it was not bad.</td>\n",
       "      <td>it was bad.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>The acting was good.</td>\n",
       "      <td>the irony is horrible.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>The music was good.</td>\n",
       "      <td>the music is horrendous.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         input                                  answer\n",
       "0          I totally loved it.              i totally hated the movie.\n",
       "1            I was really bad.                       it' s really bad.\n",
       "2             it was terrible.                         thats terrible.\n",
       "3  the acting was mostly good.  the acting is mostly horrendously bad.\n",
       "4          I liked this movie.                     i liked this movie.\n",
       "5         it was a nice movie.      this is a waste of time and money.\n",
       "6       the story was amazing.                      the story was bad.\n",
       "7              it was not bad.                             it was bad.\n",
       "8         The acting was good.                  the irony is horrible.\n",
       "9          The music was good.                the music is horrendous."
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us = [ \"I totally loved it.\",\n",
    "\"I was really bad.\",\n",
    "\"it was terrible.\",\n",
    "\"the acting was mostly good.\",\n",
    "\"I liked this movie.\",\n",
    "\"it was a nice movie.\",\n",
    "\"the story was amazing.\",\n",
    "\"it was not bad.\",\n",
    "\"The acting was good.\",\n",
    "\"The music was good.\",\n",
    "]\n",
    "\n",
    "answers = []\n",
    "saver = tf.train.Saver()\n",
    "with tf.Session(config=config) as sess:\n",
    "    saver.restore(sess, \"./\"+training_dir+'/model.ckp')\n",
    "    for u in us:\n",
    "        answers.append( MachineSays(sess,u)[0] )\n",
    "df = pd.DataFrame()\n",
    "df[\"input\"] = us\n",
    "df[\"answer\"] = answers\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lll}\n",
      "\\toprule\n",
      "{} &                        input &                                  answer \\\\\n",
      "\\midrule\n",
      "0 &          I totally loved it. &              i totally hated the movie. \\\\\n",
      "1 &            I was really bad. &                       it' s really bad. \\\\\n",
      "2 &             it was terrible. &                         thats terrible. \\\\\n",
      "3 &  the acting was mostly good. &  the acting is mostly horrendously bad. \\\\\n",
      "4 &          I liked this movie. &                     i liked this movie. \\\\\n",
      "5 &         it was a nice movie. &      this is a waste of time and money. \\\\\n",
      "6 &       the story was amazing. &                      the story was bad. \\\\\n",
      "7 &              it was not bad. &                             it was bad. \\\\\n",
      "8 &         The acting was good. &                  the irony is horrible. \\\\\n",
      "9 &          The music was good. &                the music is horrendous. \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print df.to_latex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## neighbordhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from ./logs/no_char2word/model.ckp\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>she could blow at any moment!</th>\n",
       "      <th>and their chemistry is impeccable.</th>\n",
       "      <th>a positive message from a positive film.</th>\n",
       "      <th>i was 0 when i saw it.</th>\n",
       "      <th>the girl is dying!</th>\n",
       "      <th>did they ask the fans?</th>\n",
       "      <th>i' m only a child.</th>\n",
       "      <th>this film however, is very amusing.</th>\n",
       "      <th>it' s like water.</th>\n",
       "      <th>the hillermans were a family again.</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sadly, somebody has lied to frank.</td>\n",
       "      <td>were the vietnamese all suicidal?</td>\n",
       "      <td>a virus killed 0 billion people.</td>\n",
       "      <td>what is a thief?</td>\n",
       "      <td>terrible i know.</td>\n",
       "      <td>know what else is torture?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>the girl' s reactions just seem dumb.</td>\n",
       "      <td>it' s lame!</td>\n",
       "      <td>the killers are dark with real menace.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>so well made, no cgi crap.</td>\n",
       "      <td>and the violence changes them.</td>\n",
       "      <td>impossible to improve or ignore.</td>\n",
       "      <td>i cried when i saw this sequence.</td>\n",
       "      <td>the gritty' license to kill'</td>\n",
       "      <td>did they not watch this mess?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>the worse film i have every seen.</td>\n",
       "      <td>it' s really a shame.</td>\n",
       "      <td>the world is a miserable and hard place.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>how could a film so bad be made?</td>\n",
       "      <td>and the sad thing isinternally she dies.</td>\n",
       "      <td>i prefer more vulnerable heroes.</td>\n",
       "      <td>it was hot and i was tired.</td>\n",
       "      <td>the dialogue is bad.</td>\n",
       "      <td>did they inhabit the rv?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this is a horrible film in every way.</td>\n",
       "      <td>it' s like hell.</td>\n",
       "      <td>the kids are all a mess.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>the colour is dull and grey.</td>\n",
       "      <td>and the car chase is simply amazing.</td>\n",
       "      <td>iturbi provides some fine piano playing.</td>\n",
       "      <td>i was 0 when i first saw this on tv.</td>\n",
       "      <td>this guy is a loser.</td>\n",
       "      <td>need that cult cred!</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>he' s tragic, but also elegant.</td>\n",
       "      <td>it' s like a guilty pleasure.</td>\n",
       "      <td>the lead actress here is awful.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>should i be amazed at how bad it is?</td>\n",
       "      <td>and the direction?</td>\n",
       "      <td>a masterpiece in romance filmmaking.</td>\n",
       "      <td>it was a night that i enjoyed.</td>\n",
       "      <td>there is no dialog.</td>\n",
       "      <td>did they edit out the water?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this film had feeling.</td>\n",
       "      <td>it' s like a paperweight.</td>\n",
       "      <td>the dialouge was embarrassing at times.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>the guy looks halfmad anyway.</td>\n",
       "      <td>watch the little mermaid instead.</td>\n",
       "      <td>a vehicle for michael caine.</td>\n",
       "      <td>i was 00 then.</td>\n",
       "      <td>this film has no action.</td>\n",
       "      <td>and save the day.</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this film is forever lodged in my brain.</td>\n",
       "      <td>he' s like a child.</td>\n",
       "      <td>the shyster lawyer is naturally a man.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>she could tackle any part.</td>\n",
       "      <td>and the dedication page.</td>\n",
       "      <td>my family truly enjoyed this movie.</td>\n",
       "      <td>i saw ray when it first came out.</td>\n",
       "      <td>the dialog was inane.</td>\n",
       "      <td>can i get them back?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this movie will be a favorite of mine.</td>\n",
       "      <td>it' s like a fetish!</td>\n",
       "      <td>the leading actors are a nuisance.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>should have been a 0!</td>\n",
       "      <td>nearly the entire cast is incredible.</td>\n",
       "      <td>my favorite country star is from kansas.</td>\n",
       "      <td>i gave it 0 stars.</td>\n",
       "      <td>the gore is all cgi.</td>\n",
       "      <td>do they care if we care?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this film however was mesmerizing.</td>\n",
       "      <td>it' s laughable.</td>\n",
       "      <td>the wolfgod again, apparently.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>she could be smart.</td>\n",
       "      <td>and dig the lesbian cid agents!</td>\n",
       "      <td>a fine piece of captured femininity.</td>\n",
       "      <td>i gave it 0 stars.</td>\n",
       "      <td>the girl did an okay job.</td>\n",
       "      <td>and send her to paris!</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this would' ve been a great silent film.</td>\n",
       "      <td>it' s like a wireless ad help me!</td>\n",
       "      <td>the lead actress flubbed a line?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>should children be able to enjoy a show?</td>\n",
       "      <td>are they speaking spanish?</td>\n",
       "      <td>jamie foxx transformed himself into ray.</td>\n",
       "      <td>i gave it a 00 rating.</td>\n",
       "      <td>the dialog.</td>\n",
       "      <td>dance with me?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this film deserves a wide audience.</td>\n",
       "      <td>i like' the big screen'.</td>\n",
       "      <td>there is hardly any musical score.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>should i be laughing?</td>\n",
       "      <td>and the other is swinging a machete.</td>\n",
       "      <td>typical score for eighties action movies.</td>\n",
       "      <td>i wasn' t sure that i was getting.</td>\n",
       "      <td>the giggling.</td>\n",
       "      <td>does he speak, can he speak?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>the film was released in 0000.</td>\n",
       "      <td>i' ll make this brief.</td>\n",
       "      <td>she looks great and has awesome costumes.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>the wind blows your eyes far away.</td>\n",
       "      <td>and the plot is intriguing.</td>\n",
       "      <td>a postrevolutionary movie.</td>\n",
       "      <td>i was 00.</td>\n",
       "      <td>the second is all in good time.</td>\n",
       "      <td>and she takes the bait.</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>there' s a lot visually to like.</td>\n",
       "      <td>i' d like that.</td>\n",
       "      <td>the locations in europe are awesome 0.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>the soundtrack also deserves a few words.</td>\n",
       "      <td>and there are movies which make lives.</td>\n",
       "      <td>fair to mediocre best sums up this film.</td>\n",
       "      <td>i couldn' t watch it to the end.</td>\n",
       "      <td>the girls in bathing suits.</td>\n",
       "      <td>and she needs a better haircut.</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this film to me is a very good film!</td>\n",
       "      <td>he' s tyler.</td>\n",
       "      <td>she loved it and always watched it.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>should have been titled' balderdash!</td>\n",
       "      <td>and the script is a nightmare.</td>\n",
       "      <td>it oozes laziness from its every frame.</td>\n",
       "      <td>i was told it was prince.</td>\n",
       "      <td>the dialogue is turgid.</td>\n",
       "      <td>and it does happen in the real world.</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this film, however, is a void.</td>\n",
       "      <td>this film had neither.</td>\n",
       "      <td>should have and x rating!</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>the dvd looks sounds amazing.</td>\n",
       "      <td>and the creepy chase begins again.</td>\n",
       "      <td>i pictured wendy much differently.</td>\n",
       "      <td>it was a big hit when it came out.</td>\n",
       "      <td>ted in gilbert, a</td>\n",
       "      <td>did they use contacts?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this, however, is altogether different.</td>\n",
       "      <td>it' s like that guy.</td>\n",
       "      <td>the language is awesome and passionate.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>this could have been a much better film.</td>\n",
       "      <td>and the photography is quiet nice.</td>\n",
       "      <td>a must for every family video collection.</td>\n",
       "      <td>0 reared it' s hideous head.</td>\n",
       "      <td>he got his kid back.</td>\n",
       "      <td>did they use contacts?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this movie was well done in all respects.</td>\n",
       "      <td>it' s called taste.</td>\n",
       "      <td>she plays a diner waitress.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>she could do it all.</td>\n",
       "      <td>at least the director did his research!</td>\n",
       "      <td>basically everything is over the top.</td>\n",
       "      <td>we wait with him.</td>\n",
       "      <td>that did it.</td>\n",
       "      <td>we know that already.</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>the film works best on a big screen.</td>\n",
       "      <td>it' s called taste.</td>\n",
       "      <td>the soldiers aren' t realistic.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>this could have been so much fun!</td>\n",
       "      <td>and the change is great.</td>\n",
       "      <td>a uwe boll film and positive comments?</td>\n",
       "      <td>a woman with a secret.</td>\n",
       "      <td>the dialog?</td>\n",
       "      <td>did the navy have ltas there?</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>the film seems rather dated now in 0000.</td>\n",
       "      <td>i love salma hayek.</td>\n",
       "      <td>she already had traci fingered.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>this should become a cult favorite.</td>\n",
       "      <td>and the soviet trams still in service.</td>\n",
       "      <td>emily blunt is perfect as victoria.</td>\n",
       "      <td>i saw this 00 years ago on pbs.</td>\n",
       "      <td>this film had neither.</td>\n",
       "      <td>and the same goes with dave.</td>\n",
       "      <td>i' m only a child.</td>\n",
       "      <td>this movie feels like a film project.</td>\n",
       "      <td>it' s all in vick' s head!</td>\n",
       "      <td>thomas gomez is always reliable.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                she could blow at any moment!  \\\n",
       "0          sadly, somebody has lied to frank.   \n",
       "1                  so well made, no cgi crap.   \n",
       "2            how could a film so bad be made?   \n",
       "3                the colour is dull and grey.   \n",
       "4        should i be amazed at how bad it is?   \n",
       "5               the guy looks halfmad anyway.   \n",
       "6                  she could tackle any part.   \n",
       "7                       should have been a 0!   \n",
       "8                         she could be smart.   \n",
       "9    should children be able to enjoy a show?   \n",
       "10                      should i be laughing?   \n",
       "11         the wind blows your eyes far away.   \n",
       "12  the soundtrack also deserves a few words.   \n",
       "13       should have been titled' balderdash!   \n",
       "14              the dvd looks sounds amazing.   \n",
       "15   this could have been a much better film.   \n",
       "16                       she could do it all.   \n",
       "17          this could have been so much fun!   \n",
       "18        this should become a cult favorite.   \n",
       "19                                              \n",
       "\n",
       "          and their chemistry is impeccable.  \\\n",
       "0          were the vietnamese all suicidal?   \n",
       "1             and the violence changes them.   \n",
       "2   and the sad thing isinternally she dies.   \n",
       "3       and the car chase is simply amazing.   \n",
       "4                         and the direction?   \n",
       "5          watch the little mermaid instead.   \n",
       "6                   and the dedication page.   \n",
       "7      nearly the entire cast is incredible.   \n",
       "8            and dig the lesbian cid agents!   \n",
       "9                 are they speaking spanish?   \n",
       "10      and the other is swinging a machete.   \n",
       "11               and the plot is intriguing.   \n",
       "12    and there are movies which make lives.   \n",
       "13            and the script is a nightmare.   \n",
       "14        and the creepy chase begins again.   \n",
       "15        and the photography is quiet nice.   \n",
       "16   at least the director did his research!   \n",
       "17                  and the change is great.   \n",
       "18    and the soviet trams still in service.   \n",
       "19                                             \n",
       "\n",
       "     a positive message from a positive film.  \\\n",
       "0            a virus killed 0 billion people.   \n",
       "1            impossible to improve or ignore.   \n",
       "2            i prefer more vulnerable heroes.   \n",
       "3    iturbi provides some fine piano playing.   \n",
       "4        a masterpiece in romance filmmaking.   \n",
       "5                a vehicle for michael caine.   \n",
       "6         my family truly enjoyed this movie.   \n",
       "7    my favorite country star is from kansas.   \n",
       "8        a fine piece of captured femininity.   \n",
       "9    jamie foxx transformed himself into ray.   \n",
       "10  typical score for eighties action movies.   \n",
       "11                 a postrevolutionary movie.   \n",
       "12   fair to mediocre best sums up this film.   \n",
       "13    it oozes laziness from its every frame.   \n",
       "14         i pictured wendy much differently.   \n",
       "15  a must for every family video collection.   \n",
       "16      basically everything is over the top.   \n",
       "17     a uwe boll film and positive comments?   \n",
       "18        emily blunt is perfect as victoria.   \n",
       "19                                              \n",
       "\n",
       "                  i was 0 when i saw it.               the girl is dying!  \\\n",
       "0                       what is a thief?                 terrible i know.   \n",
       "1      i cried when i saw this sequence.     the gritty' license to kill'   \n",
       "2            it was hot and i was tired.             the dialogue is bad.   \n",
       "3   i was 0 when i first saw this on tv.             this guy is a loser.   \n",
       "4         it was a night that i enjoyed.              there is no dialog.   \n",
       "5                         i was 00 then.         this film has no action.   \n",
       "6      i saw ray when it first came out.            the dialog was inane.   \n",
       "7                     i gave it 0 stars.             the gore is all cgi.   \n",
       "8                     i gave it 0 stars.        the girl did an okay job.   \n",
       "9                 i gave it a 00 rating.                      the dialog.   \n",
       "10    i wasn' t sure that i was getting.                    the giggling.   \n",
       "11                             i was 00.  the second is all in good time.   \n",
       "12      i couldn' t watch it to the end.      the girls in bathing suits.   \n",
       "13             i was told it was prince.          the dialogue is turgid.   \n",
       "14    it was a big hit when it came out.                ted in gilbert, a   \n",
       "15          0 reared it' s hideous head.             he got his kid back.   \n",
       "16                     we wait with him.                     that did it.   \n",
       "17                a woman with a secret.                      the dialog?   \n",
       "18       i saw this 00 years ago on pbs.           this film had neither.   \n",
       "19                                                                          \n",
       "\n",
       "                   did they ask the fans?  i' m only a child.  \\\n",
       "0              know what else is torture?  i' m only a child.   \n",
       "1           did they not watch this mess?  i' m only a child.   \n",
       "2                did they inhabit the rv?  i' m only a child.   \n",
       "3                    need that cult cred!  i' m only a child.   \n",
       "4            did they edit out the water?  i' m only a child.   \n",
       "5                       and save the day.  i' m only a child.   \n",
       "6                    can i get them back?  i' m only a child.   \n",
       "7                do they care if we care?  i' m only a child.   \n",
       "8                  and send her to paris!  i' m only a child.   \n",
       "9                          dance with me?  i' m only a child.   \n",
       "10           does he speak, can he speak?  i' m only a child.   \n",
       "11                and she takes the bait.  i' m only a child.   \n",
       "12        and she needs a better haircut.  i' m only a child.   \n",
       "13  and it does happen in the real world.  i' m only a child.   \n",
       "14                 did they use contacts?  i' m only a child.   \n",
       "15                 did they use contacts?  i' m only a child.   \n",
       "16                  we know that already.  i' m only a child.   \n",
       "17          did the navy have ltas there?  i' m only a child.   \n",
       "18           and the same goes with dave.  i' m only a child.   \n",
       "19                                                              \n",
       "\n",
       "          this film however, is very amusing.  \\\n",
       "0       the girl' s reactions just seem dumb.   \n",
       "1           the worse film i have every seen.   \n",
       "2       this is a horrible film in every way.   \n",
       "3             he' s tragic, but also elegant.   \n",
       "4                      this film had feeling.   \n",
       "5    this film is forever lodged in my brain.   \n",
       "6      this movie will be a favorite of mine.   \n",
       "7          this film however was mesmerizing.   \n",
       "8    this would' ve been a great silent film.   \n",
       "9         this film deserves a wide audience.   \n",
       "10             the film was released in 0000.   \n",
       "11           there' s a lot visually to like.   \n",
       "12       this film to me is a very good film!   \n",
       "13             this film, however, is a void.   \n",
       "14    this, however, is altogether different.   \n",
       "15  this movie was well done in all respects.   \n",
       "16       the film works best on a big screen.   \n",
       "17   the film seems rather dated now in 0000.   \n",
       "18      this movie feels like a film project.   \n",
       "19                                              \n",
       "\n",
       "                    it' s like water.  \\\n",
       "0                         it' s lame!   \n",
       "1               it' s really a shame.   \n",
       "2                    it' s like hell.   \n",
       "3       it' s like a guilty pleasure.   \n",
       "4           it' s like a paperweight.   \n",
       "5                 he' s like a child.   \n",
       "6                it' s like a fetish!   \n",
       "7                    it' s laughable.   \n",
       "8   it' s like a wireless ad help me!   \n",
       "9            i like' the big screen'.   \n",
       "10             i' ll make this brief.   \n",
       "11                    i' d like that.   \n",
       "12                       he' s tyler.   \n",
       "13             this film had neither.   \n",
       "14               it' s like that guy.   \n",
       "15                it' s called taste.   \n",
       "16                it' s called taste.   \n",
       "17                i love salma hayek.   \n",
       "18         it' s all in vick' s head!   \n",
       "19                                      \n",
       "\n",
       "          the hillermans were a family again.  \n",
       "0      the killers are dark with real menace.  \n",
       "1    the world is a miserable and hard place.  \n",
       "2                    the kids are all a mess.  \n",
       "3             the lead actress here is awful.  \n",
       "4     the dialouge was embarrassing at times.  \n",
       "5      the shyster lawyer is naturally a man.  \n",
       "6          the leading actors are a nuisance.  \n",
       "7              the wolfgod again, apparently.  \n",
       "8            the lead actress flubbed a line?  \n",
       "9          there is hardly any musical score.  \n",
       "10  she looks great and has awesome costumes.  \n",
       "11     the locations in europe are awesome 0.  \n",
       "12        she loved it and always watched it.  \n",
       "13                  should have and x rating!  \n",
       "14    the language is awesome and passionate.  \n",
       "15                she plays a diner waitress.  \n",
       "16            the soldiers aren' t realistic.  \n",
       "17            she already had traci fingered.  \n",
       "18           thomas gomez is always reliable.  \n",
       "19                                             "
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us = [ \"I totally loved it.\",\n",
    "\"I was really bad.\",\n",
    "\"it was terrible.\",\n",
    "\"the acting was mostly good.\",\n",
    "\"I liked this movie.\",\n",
    "\"it was a nice movie.\",\n",
    "\"the story was amazing.\",\n",
    "\"it was not bad.\",\n",
    "\"The acting was good.\",\n",
    "\"The music was good.\",\n",
    "]\n",
    "\n",
    "saver = tf.train.Saver()\n",
    "df = pd.DataFrame()\n",
    "with tf.Session(config=config) as sess:\n",
    "    saver.restore(sess, \"./\"+training_dir+'/model.ckp')\n",
    "    #for _ in range(20):\n",
    "    for u in us:\n",
    "        k = int(np.random.random() * len(sentences))\n",
    "        u = encoderDecoder.prettyDecode(sentences[k])\n",
    "        l = MachineSays(sess,u,20)\n",
    "        while len(l) < 20:\n",
    "            l.append(\"\")\n",
    "        df[u] = l\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{lllllllllll}\n",
      "\\toprule\n",
      "{} &               carla finally gets laid. &           he is gunna be big in hollywood. &      this is one of them. &      warning this could spoil your movie. &                 plot twists? &    this film shows a pirate hero a little! &     yikes! &       disappointed. &         i rate this film capital f minus. &              he should be a star. \\\\\n",
      "\\midrule\n",
      "0  &                 cheated on all fronts! &         his fear was because of his guilt. &      this is one of them. &       guess what it took to kill killjoy? &                plain stupid! &      this film is so bad that its painful. &     yikes! &       disappointed. &        i hate this film with a vengeance. &                 he' s flat wrong. \\\\\n",
      "1  &          charming film but naive film. &     he is neither a good man or a bad man. &      this is one of them. &    watch this movie forget your troubles. &             plain stupidity? &       this movie was horrible, simply put. &     yikes! &         disappoint. &       although i missed the last episode. &             he should be ashamed. \\\\\n",
      "2  &  well and culmination fight full orgy. &  he is driven to find and stop the killer. &      this is one of them. &           what is wrong with some of you? &         the plot was stupid. &      this movie is also very sad at times. &     yikes! &     disappointment. &   a cry in the dark is likewise clinical. &             we should be ashamed. \\\\\n",
      "3  &        walker warns pilot about sheba. &     he is uproarious, daring, and moronic. &      this is one of them. &              watch this at your own risk. &          the plot is stupid. &    this film shook me when i first saw it. &     yikes! &      disappointing. &         i rate this movie a very fair 00. &             she looks up in fear. \\\\\n",
      "4  &                   randall and fischer? &                    he had no getup and go. &      this is one of them. &         watch this film at your own risk! &          the plot is stupid. &         this film has other flaws as well. &     yikes! &      disappointing. &                   i rate this film a 000. &         he should not be trusted. \\\\\n",
      "5  &      raul julia as general santa anna. &    he is a spoiled brat and it bothers me. &      this is one of them. &           watch this with your soul mate. &          the plot is stupid. &     this film should be rated t for tripe. &     yikes! &      disappointing. &                   i rate this film a 000. &       he looks old and lethargic. \\\\\n",
      "6  &   was below standards, even for a fan. &              he does great job as riddick. &      this is one of them. &   raisuli what kind of rifle does he use? &           pretty stupid, eh? &     this film came right on time actually. &     yikes! &      disappointing. &                   i rate this film a 000. &            he looks about thirty. \\\\\n",
      "7  &      wang lee hom is absolutely great. &             it has dialog with bite in it. &      this is one of them. &                    random shots of dolls. &          flip on the lights? &     this film should have made them stars. &     yikes! &      disappointing. &                 with all the ingredients. &              who is julia to her? \\\\\n",
      "8  &              carole landis fares best. &       he' s an adult going to high school. &      this is one of them. &          wait till it comes out on cable. &          pwog fits the bill. &        this film looks so fresh and smart. &     yikes! &       disappointed! &       i saw this title again on shemaroo. &                  he looks around. \\\\\n",
      "9  &                 secluded and peaceful. &               so he drives off a building? &  this is not one of them. &      fans will spend tons of money on it. &            blessings to all. &         this movie was absolutely ghastly! &     yikes! &         disturbing. &         i watched this film version of r. &                  he looks around. \\\\\n",
      "10 &                   hardly anyone talks. &                it' d rule and you know it. &  this is not one of them. &     watch it with someone you truly love. &       please rent this film. &      this film shows all of that and more. &     yikes! &          delicious. &            all the acting is magnificent. &                 he shouldn' t be. \\\\\n",
      "11 &                 screenplay by james l. &             his family owns a local diner. &  this is not one of them. &                 random shots of children. &                    fullstop. &        this film is class pure and simple. &     yikes! &    dir glenn mcquai &                    i rate this movie a 0. &                 she looks upward. \\\\\n",
      "12 &                 dallas all over again. &        he is finally bond in a video game! &         this is one of t. &     watch this movie you should enjoy it. &                from the sas? &             she is simply put, his savior. &     yikes! &   dialogue editing. &        i played that back in junior high. &             he wouldn' t, period. \\\\\n",
      "13 &               wonderfully atmospheric. &                      he is good in comedy. &     this was one of them. &    characters start to live in the movie. &  plan to return to it at 00. &           she plays a prissy little tramp. &     yikes! &            silence. &  i caught this film late at night on hbo. &                   should be shot. \\\\\n",
      "14 &       hydrogen filled flying bladders? &                                         g. &     this is one of those. &       garfield was slimmed down somewhat. &                   flush now. &           this film surprised me a little. &     yikes! &            silence. &                   i gave this film a one. &      this will be somewhat short. \\\\\n",
      "15 &   wonderfully acted and superbly cast. &                                         g. &     this is one of those. &           watch this film with your kids. &  plus the dogs are cute too. &           this stuff happens all the time. &  yakitate! &     sidney poitier. &                      i rate this film 00. &              how to tell a story? \\\\\n",
      "16 &       stanley yelnats iii henry winkle &                                         g. &     this is one of those. &        giants too, some of us may recall. &        formulaic to the max. &   this movie starts slow, then tapers off. &  yakitate! &  kids flying kites. &               wait till it appears on tv. &         he also paints with love. \\\\\n",
      "17 &                    warming and humble. &                        he is a good actor. &     this is one of those. &  and the list of whoppers goes on and on. &  also props to this website! &  the film sags a bit during the third act. &     yikes. &      sidesplitting. &            i caught it last night on tmc. &               he is too talented! \\\\\n",
      "18 &                     dallas leads 0000. &               he is good and exudes charm. &     this is one of those. &           all the stunt work is gorgeous. &               plot spoilers! &  this movie was quite a pleasant surprise. &     yikes. &         delusional. &          i gave this movie a rating of 0. &  her two male foils act well too. \\\\\n",
      "19 &                                        &                                            &                           &                                           &                              &                                            &            &                     &                                           &                                   \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print df.to_latex()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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