Relation_Extraction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "\"\"\"Multi-threaded word2vec unbatched skip-gram model.\n",
    "Trains the model described in:\n",
    "(Mikolov, et. al.) Efficient Estimation of Word Representations in Vector Space\n",
    "ICLR 2013.\n",
    "http://arxiv.org/abs/1301.3781\n",
    "This model does true SGD (i.e. no minibatching). To do this efficiently, custom\n",
    "ops are used to sequentially process data within a 'batch'.\n",
    "The key ops used are:\n",
    "* skipgram custom op that does input processing.\n",
    "* neg_train custom op that efficiently calculates and applies the gradient using\n",
    "  true SGD.\n",
    "\"\"\"\n",
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "\n",
    "import os\n",
    "import sys\n",
    "import threading\n",
    "import time\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.decomposition import PCA\n",
    "from random import choice, shuffle\n",
    "from matplotlib import pylab\n",
    "import pickle\n",
    "%matplotlib inline\n",
    "\n",
    "from six.moves import xrange  # pylint: disable=redefined-builtin\n",
    "\n",
    "import numpy as np\n",
    "from numpy import array\n",
    "import pandas as pd\n",
    "import tensorflow as tf\n",
    "\n",
    "from tensorflow.models.embedding import gen_word2vec as word2vec\n",
    "\n",
    "flags = tf.app.flags\n",
    "\n",
    "flags.DEFINE_string(\"save_path\", \"./mdl\", \"Directory to write the model.\")\n",
    "flags.DEFINE_string( ## /Users/orpaz/Desktop/CS269_Relational_learning/project/20_newsgroups/sci.space/outfull\n",
    "    \"train_data\", \"./text8\",\n",
    "    \"Training data. E.g., unzipped file http://mattmahoney.net/dc/text8.zip.\")\n",
    "flags.DEFINE_string(\n",
    "    \"eval_data\", \"./word2vec/trunk/questions-words.txt\", \"Analogy questions. \"\n",
    "    \"See README.md for how to get 'questions-words.txt'.\")\n",
    "flags.DEFINE_integer(\"embedding_size\", 200, \"The embedding dimension size.\")\n",
    "flags.DEFINE_integer(\n",
    "    \"epochs_to_train\", 40,\n",
    "    \"Number of epochs to train. Each epoch processes the training data once \"\n",
    "    \"completely.\")\n",
    "flags.DEFINE_float(\"learning_rate\", 0.025, \"Initial learning rate.\")\n",
    "flags.DEFINE_integer(\"num_neg_samples\", 25,\n",
    "                     \"Negative samples per training example.\")\n",
    "flags.DEFINE_integer(\"batch_size\", 50,\n",
    "                     \"Numbers of training examples each step processes \"\n",
    "                     \"(no minibatching).\")\n",
    "flags.DEFINE_integer(\"concurrent_steps\", 12,\n",
    "                     \"The number of concurrent training steps.\")\n",
    "flags.DEFINE_integer(\"window_size\", 5,\n",
    "                     \"The number of words to predict to the left and right \"\n",
    "                     \"of the target word.\")\n",
    "flags.DEFINE_integer(\"min_count\", 5,\n",
    "                     \"The minimum number of word occurrences for it to be \"\n",
    "                     \"included in the vocabulary.\")\n",
    "flags.DEFINE_float(\"subsample\", 1e-3,\n",
    "                   \"Subsample threshold for word occurrence. Words that appear \"\n",
    "                   \"with higher frequency will be randomly down-sampled. Set \"\n",
    "                   \"to 0 to disable.\")\n",
    "flags.DEFINE_boolean(\n",
    "    \"interactive\", False,\n",
    "    \"If true, enters an IPython interactive session to play with the trained \"\n",
    "    \"model. E.g., try model.analogy(b'france', b'paris', b'russia') and \"\n",
    "    \"model.nearby([b'proton', b'elephant', b'maxwell'])\")\n",
    "\n",
    "FLAGS = flags.FLAGS\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class Options(object):\n",
    "  \"\"\"Options used by our word2vec model.\"\"\"\n",
    "\n",
    "  def __init__(self):\n",
    "    # Model options.\n",
    "\n",
    "    # Embedding dimension.\n",
    "    self.emb_dim = FLAGS.embedding_size\n",
    "\n",
    "    # Training options.\n",
    "\n",
    "    # The training text file.\n",
    "    self.train_data = FLAGS.train_data\n",
    "\n",
    "    # Number of negative samples per example.\n",
    "    self.num_samples = FLAGS.num_neg_samples\n",
    "\n",
    "    # The initial learning rate.\n",
    "    self.learning_rate = FLAGS.learning_rate\n",
    "\n",
    "    # Number of epochs to train. After these many epochs, the learning\n",
    "    # rate decays linearly to zero and the training stops.\n",
    "    self.epochs_to_train = FLAGS.epochs_to_train\n",
    "\n",
    "    # Concurrent training steps.\n",
    "    self.concurrent_steps = FLAGS.concurrent_steps\n",
    "\n",
    "    # Number of examples for one training step.\n",
    "    self.batch_size = FLAGS.batch_size\n",
    "\n",
    "    # The number of words to predict to the left and right of the target word.\n",
    "    self.window_size = FLAGS.window_size\n",
    "\n",
    "    # The minimum number of word occurrences for it to be included in the\n",
    "    # vocabulary.\n",
    "    self.min_count = FLAGS.min_count\n",
    "\n",
    "    # Subsampling threshold for word occurrence.\n",
    "    self.subsample = FLAGS.subsample\n",
    "\n",
    "    # Where to write out summaries.\n",
    "    self.save_path = FLAGS.save_path\n",
    "\n",
    "    # Eval options.\n",
    "\n",
    "    # The text file for eval.\n",
    "    self.eval_data = FLAGS.eval_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class Word2Vec(object):\n",
    "  \"\"\"Word2Vec model (Skipgram).\"\"\"\n",
    "\n",
    "  def __init__(self, options, session):\n",
    "    self._options = options\n",
    "    self._session = session\n",
    "    self._word2id = {}\n",
    "    self._id2word = []\n",
    "    self.build_graph()\n",
    "    self.build_eval_graph()\n",
    "    self.save_vocab()\n",
    "\n",
    "  def read_analogies(self):\n",
    "    \"\"\"Reads through the analogy question file.\n",
    "    Returns:\n",
    "      questions: a [n, 4] numpy array containing the analogy question's\n",
    "                 word ids.\n",
    "      questions_skipped: questions skipped due to unknown words.\n",
    "    \"\"\"\n",
    "    questions = []\n",
    "    questions_skipped = 0\n",
    "    with open(self._options.eval_data, \"rb\") as analogy_f:\n",
    "      for line in analogy_f:\n",
    "        if line.startswith(b\":\"):  # Skip comments.\n",
    "          continue\n",
    "        words = line.strip().lower().split(b\" \")\n",
    "        ids = [self._word2id.get(w.strip()) for w in words]\n",
    "        if None in ids or len(ids) != 4:\n",
    "          questions_skipped += 1\n",
    "        else:\n",
    "          questions.append(np.array(ids))\n",
    "    print(\"Eval analogy file: \", self._options.eval_data)\n",
    "    print(\"Questions: \", len(questions))\n",
    "    print(\"Skipped: \", questions_skipped)\n",
    "    self._analogy_questions = np.array(questions, dtype=np.int32)\n",
    "\n",
    "  def build_graph(self):\n",
    "    \"\"\"Build the model graph.\"\"\"\n",
    "    opts = self._options\n",
    "\n",
    "    # The training data. A text file.\n",
    "    (words, counts, words_per_epoch, current_epoch, total_words_processed,\n",
    "     examples, labels) = word2vec.skipgram(filename=opts.train_data,\n",
    "                                           batch_size=opts.batch_size,\n",
    "                                           window_size=opts.window_size,\n",
    "                                           min_count=opts.min_count,\n",
    "                                           subsample=opts.subsample)\n",
    "    (opts.vocab_words, opts.vocab_counts,\n",
    "     opts.words_per_epoch) = self._session.run([words, counts, words_per_epoch])\n",
    "    opts.vocab_size = len(opts.vocab_words)\n",
    "    print(\"Data file: \", opts.train_data)\n",
    "    print(\"Vocab size: \", opts.vocab_size - 1, \" + UNK\")\n",
    "    print(\"Words per epoch: \", opts.words_per_epoch)\n",
    "\n",
    "    self._id2word = opts.vocab_words\n",
    "    for i, w in enumerate(self._id2word):\n",
    "      self._word2id[w] = i\n",
    "\n",
    "    # Declare all variables we need.\n",
    "    # Input words embedding: [vocab_size, emb_dim]\n",
    "    w_in = tf.Variable(\n",
    "        tf.random_uniform(\n",
    "            [opts.vocab_size,\n",
    "             opts.emb_dim], -0.5 / opts.emb_dim, 0.5 / opts.emb_dim),\n",
    "        name=\"w_in\")\n",
    "\n",
    "    # Global step: scalar, i.e., shape [].\n",
    "    w_out = tf.Variable(tf.zeros([opts.vocab_size, opts.emb_dim]), name=\"w_out\")\n",
    "\n",
    "    # Global step: []\n",
    "    global_step = tf.Variable(0, name=\"global_step\")\n",
    "\n",
    "    # Linear learning rate decay.\n",
    "    words_to_train = float(opts.words_per_epoch * opts.epochs_to_train)\n",
    "    lr = opts.learning_rate * tf.maximum(\n",
    "        0.0001,\n",
    "        1.0 - tf.cast(total_words_processed, tf.float32) / words_to_train)\n",
    "\n",
    "    # Training nodes.\n",
    "    inc = global_step.assign_add(1)\n",
    "    with tf.control_dependencies([inc]):\n",
    "      train = word2vec.neg_train(w_in,\n",
    "                                 w_out,\n",
    "                                 examples,\n",
    "                                 labels,\n",
    "                                 lr,\n",
    "                                 vocab_count=opts.vocab_counts.tolist(),\n",
    "                                 num_negative_samples=opts.num_samples)\n",
    "\n",
    "    self._w_in = w_in\n",
    "    self._examples = examples\n",
    "    self._labels = labels\n",
    "    self._lr = lr\n",
    "    self._train = train\n",
    "    self.global_step = global_step\n",
    "    self._epoch = current_epoch\n",
    "    self._words = total_words_processed\n",
    "\n",
    "  def save_vocab(self):\n",
    "    \"\"\"Save the vocabulary to a file so the model can be reloaded.\"\"\"\n",
    "    opts = self._options\n",
    "    with open(os.path.join(opts.save_path, \"vocab.txt\"), \"w\") as f:\n",
    "      for i in xrange(opts.vocab_size):\n",
    "        vocab_word = tf.compat.as_text(opts.vocab_words[i]).encode(\"utf-8\")\n",
    "        f.write(\"%s %d\\n\" % (vocab_word,\n",
    "                             opts.vocab_counts[i]))\n",
    "\n",
    "  def build_eval_graph(self):\n",
    "    \"\"\"Build the evaluation graph.\"\"\"\n",
    "    # Eval graph\n",
    "    opts = self._options\n",
    "\n",
    "    # Each analogy task is to predict the 4th word (d) given three\n",
    "    # words: a, b, c.  E.g., a=italy, b=rome, c=france, we should\n",
    "    # predict d=paris.\n",
    "\n",
    "    # The eval feeds three vectors of word ids for a, b, c, each of\n",
    "    # which is of size N, where N is the number of analogies we want to\n",
    "    # evaluate in one batch.\n",
    "    analogy_a = tf.placeholder(dtype=tf.int32)  # [N]\n",
    "    analogy_b = tf.placeholder(dtype=tf.int32)  # [N]\n",
    "    analogy_c = tf.placeholder(dtype=tf.int32)  # [N]\n",
    "\n",
    "    # Normalized word embeddings of shape [vocab_size, emb_dim].\n",
    "    nemb = tf.nn.l2_normalize(self._w_in, 1)\n",
    "\n",
    "    # Each row of a_emb, b_emb, c_emb is a word's embedding vector.\n",
    "    # They all have the shape [N, emb_dim]\n",
    "    a_emb = tf.gather(nemb, analogy_a)  # a's embs\n",
    "    b_emb = tf.gather(nemb, analogy_b)  # b's embs\n",
    "    c_emb = tf.gather(nemb, analogy_c)  # c's embs\n",
    "\n",
    "    # We expect that d's embedding vectors on the unit hyper-sphere is\n",
    "    # near: c_emb + (b_emb - a_emb), which has the shape [N, emb_dim].\n",
    "    target = c_emb + (b_emb - a_emb)\n",
    "\n",
    "    # Compute cosine distance between each pair of target and vocab.\n",
    "    # dist has shape [N, vocab_size].\n",
    "    dist = tf.matmul(target, nemb, transpose_b=True)\n",
    "\n",
    "    # For each question (row in dist), find the top 4 words.\n",
    "    _, pred_idx = tf.nn.top_k(dist, 4)\n",
    "\n",
    "    # Nodes for computing neighbors for a given word according to\n",
    "    # their cosine distance.\n",
    "    nearby_word = tf.placeholder(dtype=tf.int32)  # word id\n",
    "    nearby_emb = tf.gather(nemb, nearby_word)\n",
    "    nearby_dist = tf.matmul(nearby_emb, nemb, transpose_b=True)\n",
    "    nearby_val, nearby_idx = tf.nn.top_k(nearby_dist,\n",
    "                                         min(1000, opts.vocab_size))\n",
    "\n",
    "    # Nodes in the construct graph which are used by training and\n",
    "    # evaluation to run/feed/fetch.\n",
    "    self._analogy_a = analogy_a\n",
    "    self._analogy_b = analogy_b\n",
    "    self._analogy_c = analogy_c\n",
    "    self._analogy_pred_idx = pred_idx\n",
    "    self._nearby_word = nearby_word\n",
    "    self._nearby_val = nearby_val\n",
    "    self._nearby_idx = nearby_idx\n",
    "\n",
    "    # Properly initialize all variables.\n",
    "    tf.initialize_all_variables().run()\n",
    "\n",
    "    self.saver = tf.train.Saver()\n",
    "\n",
    "  def _train_thread_body(self):\n",
    "    initial_epoch, = self._session.run([self._epoch])\n",
    "    while True:\n",
    "      _, epoch = self._session.run([self._train, self._epoch])\n",
    "      if epoch != initial_epoch:\n",
    "        break\n",
    "\n",
    "  def train(self):\n",
    "    \"\"\"Train the model.\"\"\"\n",
    "    opts = self._options\n",
    "\n",
    "    initial_epoch, initial_words = self._session.run([self._epoch, self._words])\n",
    "\n",
    "    workers = []\n",
    "    for _ in xrange(opts.concurrent_steps):\n",
    "      t = threading.Thread(target=self._train_thread_body)\n",
    "      t.start()\n",
    "      workers.append(t)\n",
    "\n",
    "    last_words, last_time = initial_words, time.time()\n",
    "    while True:\n",
    "      time.sleep(5)  # Reports our progress once a while.\n",
    "      (epoch, step, words, lr) = self._session.run(\n",
    "          [self._epoch, self.global_step, self._words, self._lr])\n",
    "      now = time.time()\n",
    "      last_words, last_time, rate = words, now, (words - last_words) / (\n",
    "          now - last_time)\n",
    "      print(\"Epoch %4d Step %8d: lr = %5.3f words/sec = %8.0f\\r\" % (epoch, step,\n",
    "                                                                    lr, rate),\n",
    "            end=\"\")\n",
    "      sys.stdout.flush()\n",
    "      if epoch != initial_epoch:\n",
    "        break\n",
    "\n",
    "    for t in workers:\n",
    "      t.join()\n",
    "\n",
    "  def _predict(self, analogy):\n",
    "    \"\"\"Predict the top 4 answers for analogy questions.\"\"\"\n",
    "    idx, = self._session.run([self._analogy_pred_idx], {\n",
    "        self._analogy_a: analogy[:, 0],\n",
    "        self._analogy_b: analogy[:, 1],\n",
    "        self._analogy_c: analogy[:, 2]\n",
    "    })\n",
    "    return idx\n",
    "\n",
    "  def eval(self):\n",
    "    \"\"\"Evaluate analogy questions and reports accuracy.\"\"\"\n",
    "\n",
    "    # How many questions we get right at precision@1.\n",
    "    correct = 0\n",
    "\n",
    "    try:\n",
    "      total = self._analogy_questions.shape[0]\n",
    "    except AttributeError as e:\n",
    "      raise AttributeError(\"Need to read analogy questions.\")\n",
    "\n",
    "    start = 0\n",
    "    while start < total:\n",
    "      limit = start + 2500\n",
    "      sub = self._analogy_questions[start:limit, :]\n",
    "      idx = self._predict(sub)\n",
    "      start = limit\n",
    "      for question in xrange(sub.shape[0]):\n",
    "        for j in xrange(4):\n",
    "          if idx[question, j] == sub[question, 3]:\n",
    "            # Bingo! We predicted correctly. E.g., [italy, rome, france, paris].\n",
    "            correct += 1\n",
    "            break\n",
    "          elif idx[question, j] in sub[question, :3]:\n",
    "            # We need to skip words already in the question.\n",
    "            continue\n",
    "          else:\n",
    "            # The correct label is not the precision@1\n",
    "            break\n",
    "    print()\n",
    "    print(\"Eval %4d/%d accuracy = %4.1f%%\" % (correct, total,\n",
    "                                              correct * 100.0 / total))\n",
    "\n",
    "  def analogy(self, w0, w1, w2):\n",
    "    \"\"\"Predict word w3 as in w0:w1 vs w2:w3.\"\"\"\n",
    "    wid = np.array([[self._word2id.get(w, 0) for w in [w0, w1, w2]]])\n",
    "    idx = self._predict(wid)\n",
    "    for c in [self._id2word[i] for i in idx[0, :]]:\n",
    "      if c not in [w0, w1, w2]:\n",
    "        print(c)\n",
    "        return w2,c\n",
    "    print(\"unknown\")\n",
    "\n",
    "  def nearby(self, words, num=20):\n",
    "    \"\"\"Prints out nearby words given a list of words.\"\"\"\n",
    "    ids = np.array([self._word2id.get(x, 0) for x in words])\n",
    "    vals, idx = self._session.run(\n",
    "        [self._nearby_val, self._nearby_idx], {self._nearby_word: ids})\n",
    "    for i in xrange(len(words)):\n",
    "      print(\"\\n%s\\n=====================================\" % (words[i]))\n",
    "      for (neighbor, distance) in zip(idx[i, :num], vals[i, :num]):\n",
    "        print(\"%-20s %6.4f\" % (self._id2word[neighbor], distance))\n",
    "    return idx\n",
    " \n",
    "  def kMeansCluster(self, num_clusters, max_num_steps, stop_coeficient = 0.0):\n",
    "      vectors = tf.constant(self._w_in.eval())\n",
    "      centroids = tf.Variable(tf.slice(tf.random_shuffle(vectors),\n",
    "                                       [0,0],[num_clusters,-1]))\n",
    "      dim = opts.emb_dim\n",
    "    \n",
    "      old_centroids = tf.Variable(tf.zeros([num_clusters,dim]))\n",
    "      centroid_distance = tf.Variable(tf.zeros([num_clusters,dim]))\n",
    "\n",
    "      expanded_vectors = tf.expand_dims(vectors, 0)\n",
    "      expanded_centroids = tf.expand_dims(centroids, 1)\n",
    "\n",
    "      print (expanded_vectors.get_shape())\n",
    "      print (expanded_centroids.get_shape())\n",
    "\n",
    "      distances = tf.reduce_sum(\n",
    "        tf.square(tf.sub(expanded_vectors, expanded_centroids)), 2)\n",
    "      assignments = tf.argmin(distances, 0)\n",
    "\n",
    "      means = tf.concat(0, [\n",
    "        tf.reduce_mean(\n",
    "            tf.gather(vectors,\n",
    "                      tf.reshape(\n",
    "                        tf.where(\n",
    "                          tf.equal(assignments, c)\n",
    "                        ),[1,-1])\n",
    "                     ),reduction_indices=[1])\n",
    "        for c in xrange(num_clusters)])\n",
    "\n",
    "      save_old_centroids = tf.assign(old_centroids, centroids)\n",
    "\n",
    "      update_centroids = tf.assign(centroids, means)\n",
    "      init_op = tf.initialize_all_variables()\n",
    "\n",
    "      performance = tf.assign(centroid_distance, tf.sub(centroids, old_centroids))\n",
    "      check_stop = tf.reduce_sum(tf.abs(performance))\n",
    "\n",
    "      with tf.Session() as sess:\n",
    "        sess.run(init_op)\n",
    "        for step in xrange(max_num_steps):\n",
    "          print (\"Running step \" + str(step))\n",
    "          sess.run(save_old_centroids)\n",
    "          _, centroid_values, assignment_values = sess.run([update_centroids,\n",
    "                                                            centroids,\n",
    "                                                            assignments])\n",
    "          sess.run(check_stop)\n",
    "          current_stop_coeficient = check_stop.eval()\n",
    "          print (\"coeficient:\", current_stop_coeficient)\n",
    "          if current_stop_coeficient <= stop_coeficient:\n",
    "            break\n",
    "        \n",
    "      return centroid_values, assignment_values\n",
    "\n",
    "  def TFKMeansCluster(self, noofclusters):\n",
    "    \"\"\"\n",
    "    K-Means Clustering using TensorFlow.\n",
    "    'vectors' should be a n*k 2-D NumPy array, where n is the number\n",
    "    of vectors of dimensionality k.\n",
    "    'noofclusters' should be an integer.\n",
    "    \"\"\"\n",
    "    \n",
    "    vectors = self._w_in.eval()\n",
    "    noofclusters = int(noofclusters)\n",
    "    assert noofclusters < len(vectors)\n",
    " \n",
    "    #Find out the dimensionality\n",
    "    dim = opts.emb_dim\n",
    " \n",
    "    #Will help select random centroids from among the available vectors\n",
    "    vector_indices = list(range(len(vectors)))\n",
    "    shuffle(vector_indices)\n",
    " \n",
    "    #GRAPH OF COMPUTATION\n",
    "    #We initialize a new graph and set it as the default during each run\n",
    "    #of this algorithm. This ensures that as this function is called\n",
    "    #multiple times, the default graph doesn't keep getting crowded with\n",
    "    #unused ops and Variables from previous function calls.\n",
    " \n",
    "    graph = tf.Graph()\n",
    " \n",
    "    with graph.as_default():\n",
    " \n",
    "        #SESSION OF COMPUTATION\n",
    " \n",
    "        sess = tf.Session()\n",
    " \n",
    "        ##CONSTRUCTING THE ELEMENTS OF COMPUTATION\n",
    " \n",
    "        ##First lets ensure we have a Variable vector for each centroid,\n",
    "        ##initialized to one of the vectors from the available data points\n",
    "        centroids = [tf.Variable((vectors[vector_indices[i]]))\n",
    "                     for i in range(noofclusters)]\n",
    "        ##These nodes will assign the centroid Variables the appropriate\n",
    "        ##values\n",
    "        centroid_value = tf.placeholder(\"float32\", [dim])\n",
    "        cent_assigns = []\n",
    "        for centroid in centroids:\n",
    "            cent_assigns.append(tf.assign(centroid, centroid_value))\n",
    " \n",
    "        ##Variables for cluster assignments of individual vectors(initialized\n",
    "        ##to 0 at first)\n",
    "        assignments = [tf.Variable(0) for i in range(len(vectors))]\n",
    "        ##These nodes will assign an assignment Variable the appropriate\n",
    "        ##value\n",
    "        assignment_value = tf.placeholder(\"int32\")\n",
    "        cluster_assigns = []\n",
    "        for assignment in assignments:\n",
    "            cluster_assigns.append(tf.assign(assignment,\n",
    "                                             assignment_value))\n",
    " \n",
    "        ##Now lets construct the node that will compute the mean\n",
    "        #The placeholder for the input\n",
    "        mean_input = tf.placeholder(\"float\", [None, dim])\n",
    "        #The Node/op takes the input and computes a mean along the 0th\n",
    "        #dimension, i.e. the list of input vectors\n",
    "        mean_op = tf.reduce_mean(mean_input, 0)\n",
    " \n",
    "        ##Node for computing Euclidean distances\n",
    "        #Placeholders for input\n",
    "        v1 = tf.placeholder(\"float\", [dim])\n",
    "        v2 = tf.placeholder(\"float\", [dim])\n",
    "        euclid_dist = tf.sqrt(tf.reduce_sum(tf.pow(tf.sub(\n",
    "            v1, v2), 2)))\n",
    " \n",
    "        ##This node will figure out which cluster to assign a vector to,\n",
    "        ##based on Euclidean distances of the vector from the centroids.\n",
    "        #Placeholder for input\n",
    "        centroid_distances = tf.placeholder(\"float\", [noofclusters])\n",
    "        cluster_assignment = tf.argmin(centroid_distances, 0)\n",
    " \n",
    "        ##INITIALIZING STATE VARIABLES\n",
    " \n",
    "        ##This will help initialization of all Variables defined with respect\n",
    "        ##to the graph. The Variable-initializer should be defined after\n",
    "        ##all the Variables have been constructed, so that each of them\n",
    "        ##will be included in the initialization.\n",
    "        init_op = tf.initialize_all_variables()\n",
    " \n",
    "        #Initialize all variables\n",
    "        sess.run(init_op)\n",
    " \n",
    "        ##CLUSTERING ITERATIONS\n",
    " \n",
    "        #Now perform the Expectation-Maximization steps of K-Means clustering\n",
    "        #iterations. To keep things simple, we will only do a set number of\n",
    "        #iterations, instead of using a Stopping Criterion.\n",
    "        noofiterations = 100\n",
    "        for iteration_n in range(noofiterations):\n",
    " \n",
    "            ##EXPECTATION STEP\n",
    "            ##Based on the centroid locations till last iteration, compute\n",
    "            ##the _expected_ centroid assignments.\n",
    "            #Iterate over each vector\n",
    "            for vector_n in range(len(vectors)):\n",
    "                vect = vectors[vector_n]\n",
    "                #Compute Euclidean distance between this vector and each\n",
    "                #centroid. Remember that this list cannot be named\n",
    "                #'centroid_distances', since that is the input to the\n",
    "                #cluster assignment node.\n",
    "                distances = [sess.run(euclid_dist, feed_dict={\n",
    "                    v1: vect, v2: sess.run(centroid)})\n",
    "                             for centroid in centroids]\n",
    "                #Now use the cluster assignment node, with the distances\n",
    "                #as the input\n",
    "                assignment = sess.run(cluster_assignment, feed_dict = {\n",
    "                    centroid_distances: distances})\n",
    "                #Now assign the value to the appropriate state variable\n",
    "                sess.run(cluster_assigns[vector_n], feed_dict={\n",
    "                    assignment_value: assignment})\n",
    " \n",
    "            ##MAXIMIZATION STEP\n",
    "            #Based on the expected state computed from the Expectation Step,\n",
    "            #compute the locations of the centroids so as to maximize the\n",
    "            #overall objective of minimizing within-cluster Sum-of-Squares\n",
    "            for cluster_n in range(noofclusters):\n",
    "                #Collect all the vectors assigned to this cluster\n",
    "                assigned_vects = [vectors[i] for i in range(len(vectors))\n",
    "                                  if sess.run(assignments[i]) == cluster_n]\n",
    "                #Compute new centroid location\n",
    "                new_location = sess.run(mean_op, feed_dict={\n",
    "                    mean_input: array(assigned_vects)})\n",
    "                #Assign value to appropriate variable\n",
    "                sess.run(cent_assigns[cluster_n], feed_dict={\n",
    "                    centroid_value: new_location})\n",
    " \n",
    "        #Return centroids and assignments\n",
    "        centroids = sess.run(centroids)\n",
    "        assignments = sess.run(assignments)\n",
    "        return centroids, assignments\n",
    "    \n",
    "  def k_means(self):   \n",
    "    K=500\n",
    "    MAX_ITERS = 10\n",
    "    opts = self._options\n",
    "    \n",
    "    start = time.time()\n",
    "    \n",
    "    # Normalized word embeddings of shape [vocab_size, emb_dim].\n",
    "    #nemb = tf.nn.l2_normalize(self._w_in, 1)\n",
    "    #points = tf.Variable(tf.random_uniform([N,2]))\n",
    "    points = self._w_in.eval()\n",
    "    cluster_assignments = tf.Variable(tf.zeros([opts.vocab_size], dtype=tf.int64))\n",
    "\n",
    "    # Silly initialization:  Use the first K points as the starting\n",
    "    # centroids.  In the real world, do this better.\n",
    "    centroids = tf.Variable(tf.slice(points, [0,0], [K,opts.emb_dim]))\n",
    "\n",
    "    # Replicate to N copies of each centroid and K copies of each\n",
    "    # point, then subtract and compute the sum of squared distances.\n",
    "    rep_centroids = tf.reshape(tf.tile(centroids, [opts.vocab_size, 1]), [opts.vocab_size, K, opts.emb_dim])\n",
    "    rep_points = tf.reshape(tf.tile(points, [1, K]), [opts.vocab_size, K, opts.emb_dim])\n",
    "    sum_squares = tf.reduce_sum(tf.square(rep_points - rep_centroids), reduction_indices=2)\n",
    "\n",
    "    # Use argmin to select the lowest-distance point\n",
    "    best_centroids = tf.argmin(sum_squares, 1)\n",
    "    did_assignments_change = tf.reduce_any(tf.not_equal(best_centroids, \n",
    "                                                        cluster_assignments))\n",
    "\n",
    "    def bucket_mean(data, bucket_ids, num_buckets):\n",
    "        total = tf.unsorted_segment_sum(data, bucket_ids, num_buckets)\n",
    "        count = tf.unsorted_segment_sum(tf.ones_like(data), bucket_ids, num_buckets)\n",
    "        return total / count\n",
    "\n",
    "    means = bucket_mean(points, best_centroids, K)\n",
    "\n",
    "    # Do not write to the assigned clusters variable until after\n",
    "    # computing whether the assignments have changed - hence with_dependencies\n",
    "    with tf.control_dependencies([did_assignments_change]):\n",
    "        do_updates = tf.group(\n",
    "            centroids.assign(means),\n",
    "            cluster_assignments.assign(best_centroids))\n",
    "\n",
    "    init = tf.initialize_all_variables()\n",
    "\n",
    "    self._session.run(init)\n",
    "\n",
    "    changed = True\n",
    "    iters = 0\n",
    "\n",
    "    while changed and iters < MAX_ITERS:\n",
    "        iters += 1\n",
    "        [changed, _] = self._session.run([did_assignments_change, do_updates])\n",
    "\n",
    "    [centers, assignments] = self._session.run([centroids, cluster_assignments])\n",
    "    end = time.time()\n",
    "    print (\"Found in %.2f seconds\" % (end-start)), iters, \"iterations\"\n",
    "    #print (\"Centroids:\")\n",
    "    #print (centers)\n",
    "    #print (\"Cluster assignments:\", assignments)\n",
    "    return centers, assignments\n",
    "\n",
    "  def plot_k_means(self, centers = None):\n",
    "    num_points = 500\n",
    "    tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=1000)\n",
    "    #nemb = tf.nn.l2_normalize(self._w_in, 1)\n",
    "    two_d_embeddings = tsne.fit_transform(self._w_in.eval()[1:num_points+1, :])\n",
    "    if centers is not None:\n",
    "        two_d_centers = tsne.fit_transform(centers)\n",
    "\n",
    "    def plot(embeddings, labels, centers = None):\n",
    "        assert embeddings.shape[0] >= len(labels), 'More labels than embeddings'\n",
    "        pylab.figure(figsize=(15,15))  # in inches\n",
    "        if centers is not None:\n",
    "            for c in centers:\n",
    "                x, y = c\n",
    "                pylab.scatter(x, y)\n",
    "                pylab.annotate(\"Cluster_middle!!!\", xy=(x, y), xytext=(5, 2), textcoords='offset points', ha='right', va='bottom')\n",
    "            pylab.scatter(x, y)\n",
    "        for i, label in enumerate(labels):\n",
    "            x, y = embeddings[i,:]\n",
    "            pylab.scatter(x, y)\n",
    "            pylab.annotate(label, xy=(x, y), xytext=(5, 2), textcoords='offset points', ha='right', va='bottom')\n",
    "        pylab.show()\n",
    "\n",
    "    words = [model._id2word[i] for i in range(1, num_points+1)]\n",
    "    if centers is not None:\n",
    "        plot(two_d_embeddings, words, two_d_centers)\n",
    "    else:\n",
    "        plot(two_d_embeddings, words)\n",
    "\n",
    "  def nearby_clusters(self, clusters, num=20):\n",
    "    opts = self._options\n",
    "    nemb = tf.nn.l2_normalize(self._w_in, 1)\n",
    "    nearby_dist = tf.matmul(clusters, nemb, transpose_b=True)\n",
    "    nearby_val, nearby_idx = tf.nn.top_k(nearby_dist, min(1000, opts.vocab_size))\n",
    "    \n",
    "    tf.initialize_all_variables().run()\n",
    "    vals, idx = self._session.run([nearby_val, nearby_idx])\n",
    "       \n",
    "    for i in xrange(len(clusters)):\n",
    "      print(\"\\n%s\\n=====================================\" % (\"clusters:\" + str(i)))\n",
    "      for (neighbor, distance) in zip(idx[i, :num], vals[i, :num]):\n",
    "        print(\"%-20s %6.4f\" % (self._id2word[neighbor], distance))\n",
    "        \n",
    "  def find_cluster_analogy(self, center1, center2, word):\n",
    "    # Normalized word embeddings of shape [vocab_size, emb_dim].\n",
    "    nemb = tf.nn.l2_normalize(self._w_in, 1)\n",
    "    w = self._word2id.get(word, 0)\n",
    "    # Each row of a_emb, b_emb, c_emb is a word's embedding vector.\n",
    "    # They all have the shape [N, emb_dim]\n",
    "    a_emb = center1\n",
    "    b_emb = center2\n",
    "    c_emb = tf.gather(nemb, w)  # c's embs\n",
    "\n",
    "    # We expect that d's embedding vectors on the unit hyper-sphere is\n",
    "    # near: c_emb + (b_emb - a_emb), which has the shape [N, emb_dim].\n",
    "    target = c_emb + (b_emb - a_emb)\n",
    "    target = tf.reshape(target,[1,-1])\n",
    "    \n",
    "    # Compute cosine distance between each pair of target and vocab.\n",
    "    # dist has shape [N, vocab_size].\n",
    "    dist = tf.matmul(target.eval(), nemb, transpose_b=True)\n",
    "\n",
    "    # For each question (row in dist), find the top 4 words.\n",
    "    _, pred_idx = tf.nn.top_k(dist, 4)\n",
    "    for c in [self._id2word[i] for i in pred_idx.eval()[0, :]]:\n",
    "      #if c not in [w0, w1, w2]:\n",
    "        print(c)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot resulting vector space "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data file:  ./text8\n",
      "Vocab size:  71290  + UNK\n",
      "Words per epoch:  17005207\n"
     ]
    },
    {
     "data": {
      "image/png": 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PfhUUFMSiRQtwuVykp6fjcrlYtGjBNVcvSi6/smZzwa+/bzZu3Mi0adNYtmwZ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QFPgX8CWwWlGU+o9orwAVWwVbIpE8VbKzs9m2bRs3btzg22+/fWT2OoDz588TEBCAEIIRI0bo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GZmolOnTkhNTYWnpyeSkpIQEhKCS5cuoUuXLoiMjOSIR3FxcWxjuV27dhgzZgy+/vrrOuVq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8iEWLFmHDhg1ITEyEgoICa3/x4sXIzMzE4MGDWWfzs2fPcPfuXaxbtw7Xrl3DxIkT2TYD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\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Lbe4qSkrK0NbWbtDCDACWy+vjx4/Rp08f9OnTB5qamhgyZAhGjhwJoNLqDwCUlZWhpqYG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EkH5owySZIkSSeVevXq7X61mP/OKANYBEBCQsIRnedYZ6aVhKVLlxZ5v2TJEhITE/ebTZae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\nkiRJgEGZJEmSJEmSBBiUS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MzMzMzMzAB3lJmZmZmZmZmZmQHuKDMzMzMzMzMzMwPcUWZm\nZmZmZmZmZga4o8zMzMzMzMzMzAxwR5mZmZmZmZmZmRngjjIzMzMzMzMzMzMA/g8boO5mFOoZJAAA\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c46dba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "opts = Options()\n",
    "with tf.Graph().as_default(), tf.Session() as session:\n",
    "    model = Word2Vec(opts, session)\n",
    "    model.saver.restore(session, os.path.join(opts.save_path, \"model.ckpt-15092945\"))\n",
    "    model.plot_k_means()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clustering, Dimension reduction and cross cluster vector extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import random\n",
    "opts = Options()\n",
    "temp = []\n",
    "with tf.Graph().as_default(), tf.Session() as session:\n",
    "    model = Word2Vec(opts, session)\n",
    "    model.saver.restore(session, os.path.join(opts.save_path, \"model.ckpt-15092945\"))\n",
    "    temp = model._w_in.eval()[res]\n",
    "    pca = PCA(n_components=None)\n",
    "    pca.fit_transform(temp)\n",
    "\n",
    "#     centers, assignments = model.kMeansCluster(200,40)\n",
    "#     with open('centers_200_40.pickle', 'wb') as f:\n",
    "#     # Pickle the 'data' dictionary using the highest protocol available.\n",
    "#       pickle.dump(centers, f, pickle.HIGHEST_PROTOCOL)\n",
    "#     with open('assignments_200_40.pickle', 'wb') as f:\n",
    "#     # Pickle the 'data' dictionary using the highest protocol available.\n",
    "#       pickle.dump(assignments, f, pickle.HIGHEST_PROTOCOL)\n",
    "#     model.plot_k_means(centers)\n",
    "#     print(model._w_in.eval()[1:3])\n",
    "#     model.nearby_clusters(centers)\n",
    "#    model.find_cluster_analogy(centers[208], centers[203], b'pilsner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pca.explained_variance_ratio_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading predefined cluters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "with open('centers_300_40.pickle', 'rb') as f:\n",
    "# Pickle the 'data' dictionary using the highest protocol available.\n",
    "  centers = pickle.load(f)\n",
    "with open('assignments_300_40.pickle', 'rb') as f:\n",
    "# Pickle the 'data' dictionary using the highest protocol available.\n",
    "  assignments = pickle.load(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### In cluster extraction & Skip cluster extraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data file:  ./text8\n",
      "Vocab size:  71290  + UNK\n",
      "Words per epoch:  17005207\n",
      "b'milkshake' b'tequila' b'yum'\n",
      "b'moshi'\n",
      "b'milkshake' b'tequila' b'stewed'\n",
      "b'beiderbecke'\n",
      "b'milkshake' b'tequila' b'garnishes'\n",
      "b'cobblers'\n",
      "b'milkshake' b'tequila' b'matzoh'\n",
      "b'discernable'\n",
      "b'milkshake' b'tequila' b'mash'\n",
      "b'smoked'\n",
      "b'milkshake' b'tequila' b'soaked'\n",
      "b'adhered'\n",
      "b'milkshake' b'tequila' b'manioc'\n",
      "b'plantains'\n",
      "b'milkshake' b'tequila' b'vegetable'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'cob'\n",
      "b'wildebeest'\n",
      "b'milkshake' b'tequila' b'pancakes'\n",
      "b'disparate'\n",
      "b'milkshake' b'tequila' b'seasoned'\n",
      "b'seafood'\n",
      "b'milkshake' b'tequila' b'soju'\n",
      "b'beiderbecke'\n",
      "b'milkshake' b'tequila' b'couscous'\n",
      "b'mestizos'\n",
      "b'milkshake' b'tequila' b'raspberries'\n",
      "b'redfish'\n",
      "b'milkshake' b'tequila' b'wordplay'\n",
      "b'disparate'\n",
      "b'milkshake' b'tequila' b'roquefort'\n",
      "b'disparate'\n",
      "b'milkshake' b'tequila' b'carne'\n",
      "b'dane'\n",
      "b'milkshake' b'tequila' b'pomace'\n",
      "b'mailer'\n",
      "b'milkshake' b'tequila' b'salad'\n",
      "b'amerika'\n",
      "b'milkshake' b'tequila' b'gastronomical'\n",
      "b'diable'\n",
      "b'milkshake' b'tequila' b'beverages'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'angostura'\n",
      "b'vermouth'\n",
      "b'milkshake' b'tequila' b'soba'\n",
      "b'udon'\n",
      "b'milkshake' b'tequila' b'gourmet'\n",
      "b'beiderbecke'\n",
      "b'milkshake' b'tequila' b'marzipan'\n",
      "b'mestizos'\n",
      "b'milkshake' b'tequila' b'greasy'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'leaven'\n",
      "b'kimbundu'\n",
      "b'milkshake' b'tequila' b'homebrewing'\n",
      "b'disparate'\n",
      "b'milkshake' b'tequila' b'maggots'\n",
      "b'worm'\n",
      "b'milkshake' b'tequila' b'distilling'\n",
      "b'drabble'\n",
      "b'milkshake' b'tequila' b'canola'\n",
      "b'discernable'\n",
      "b'milkshake' b'tequila' b'seasoning'\n",
      "b'injecting'\n",
      "b'milkshake' b'tequila' b'chunky'\n",
      "b'burroughs'\n",
      "b'milkshake' b'tequila' b'waffle'\n",
      "b'adhered'\n",
      "b'milkshake' b'tequila' b'peppers'\n",
      "b'chili'\n",
      "b'milkshake' b'tequila' b'pint'\n",
      "b'sutcliff'\n",
      "b'milkshake' b'tequila' b'liqueur'\n",
      "b'vermouth'\n",
      "b'milkshake' b'tequila' b'apricots'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'cuisines'\n",
      "b'cuisine'\n",
      "b'milkshake' b'tequila' b'lime'\n",
      "b'trel'\n",
      "b'milkshake' b'tequila' b'flavorings'\n",
      "b'purportedly'\n",
      "b'milkshake' b'tequila' b'maggots'\n",
      "b'worm'\n",
      "b'milkshake' b'tequila' b'hogs'\n",
      "b'booksellers'\n",
      "b'milkshake' b'tequila' b'ramen'\n",
      "b'udon'\n",
      "b'milkshake' b'tequila' b'liquors'\n",
      "b'discernable'\n",
      "b'milkshake' b'tequila' b'rauchbier'\n",
      "b'schlenkerla'\n",
      "b'milkshake' b'tequila' b'spoiling'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'putrefaction'\n",
      "b'inapplicable'\n",
      "b'milkshake' b'tequila' b'buckwheat'\n",
      "b'quinoa'\n",
      "b'milkshake' b'tequila' b'thickly'\n",
      "b'attesting'\n",
      "b'milkshake' b'tequila' b'horseradish'\n",
      "b'consolamentum'\n",
      "b'milkshake' b'tequila' b'liquors'\n",
      "b'discernable'\n",
      "b'milkshake' b'tequila' b'simmered'\n",
      "b'erupted'\n",
      "b'milkshake' b'tequila' b'flavoring'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'tuan'\n",
      "b'beiderbecke'\n",
      "b'milkshake' b'tequila' b'wonton'\n",
      "b'ramen'\n",
      "b'milkshake' b'tequila' b'gelatin'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'soy'\n",
      "b'tortillas'\n",
      "b'milkshake' b'tequila' b'azuki'\n",
      "b'striata'\n",
      "b'milkshake' b'tequila' b'brine'\n",
      "b'protrude'\n",
      "b'milkshake' b'tequila' b'perfumes'\n",
      "b'mestizos'\n",
      "b'milkshake' b'tequila' b'dairy'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'husk'\n",
      "b'grits'\n",
      "b'milkshake' b'tequila' b'taco'\n",
      "b'jellyfish'\n",
      "b'milkshake' b'tequila' b'drills'\n",
      "b'centipedes'\n",
      "b'milkshake' b'tequila' b'intoxicating'\n",
      "b'discernable'\n",
      "b'milkshake' b'tequila' b'spiced'\n",
      "b'reverence'\n",
      "b'milkshake' b'tequila' b'twinkies'\n",
      "b'mailer'\n",
      "b'milkshake' b'tequila' b'sprouting'\n",
      "b'popularization'\n",
      "b'milkshake' b'tequila' b'freezer'\n",
      "b'discernable'\n",
      "b'milkshake' b'tequila' b'abv'\n",
      "b'diable'\n",
      "b'milkshake' b'tequila' b'artichoke'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'tomatoes'\n",
      "b'seafood'\n",
      "b'milkshake' b'tequila' b'earthy'\n",
      "b'diable'\n",
      "b'milkshake' b'tequila' b'chillis'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'leche'\n",
      "b'disparate'\n",
      "b'milkshake' b'tequila' b'angostura'\n",
      "b'vermouth'\n",
      "b'milkshake' b'tequila' b'pancakes'\n",
      "b'disparate'\n",
      "b'milkshake' b'tequila' b'bearnaise'\n",
      "b'carthaginians'\n",
      "b'milkshake' b'tequila' b'cookbook'\n",
      "b'discordia'\n",
      "b'milkshake' b'tequila' b'tequila'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'cornmeal'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'cheeses'\n",
      "b'curd'\n",
      "b'milkshake' b'tequila' b'meaty'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'buttery'\n",
      "b'diable'\n",
      "b'milkshake' b'tequila' b'pint'\n",
      "b'sutcliff'\n",
      "b'milkshake' b'tequila' b'marinated'\n",
      "b'tortillas'\n",
      "b'milkshake' b'tequila' b'curries'\n",
      "b'diable'\n",
      "b'milkshake' b'tequila' b'crawfish'\n",
      "b'redfish'\n",
      "b'milkshake' b'tequila' b'corn'\n",
      "b'maize'\n",
      "b'milkshake' b'tequila' b'vodka'\n",
      "b'vermouth'\n",
      "b'milkshake' b'tequila' b'cookbooks'\n",
      "b'disparate'\n",
      "b'milkshake' b'tequila' b'celery'\n",
      "b'thyme'\n",
      "b'milkshake' b'tequila' b'kosher'\n",
      "b'ambergris'\n",
      "b'milkshake' b'tequila' b'lemons'\n",
      "b'mythography'\n",
      "b'milkshake' b'tequila' b'jelly'\n",
      "b'bees'\n",
      "b'milkshake' b'tequila' b'fermentable'\n",
      "b'discernable'\n",
      "b'milkshake' b'tequila' b'brewed'\n",
      "b'ales'\n",
      "b'milkshake' b'tequila' b'lager'\n",
      "b'rauchbier'\n",
      "b'milkshake' b'tequila' b'yum'\n",
      "b'moshi'\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "opts = Options()\n",
    "temp = []\n",
    "with tf.Graph().as_default(), tf.Session() as session:\n",
    "    model = Word2Vec(opts, session)\n",
    "    model.saver.restore(session, os.path.join(opts.save_path, \"model.ckpt-15092945\"))\n",
    "#     temp = model._w_in.eval()[res]\n",
    "\n",
    "#     for i in range(100):\n",
    "#         a = model._id2word[random.choice(res[0])]\n",
    "#         b = model._id2word[random.choice(res[0])]\n",
    "#         c = model._id2word[random.choice(res[0])]\n",
    "#         print(a,b,c)\n",
    "#         model.analogy(a, b, c)\n",
    "\n",
    "#     vals = model.nearby([b'russia'])\n",
    "    a = model._id2word[random.choice(res[0])]\n",
    "    b = model._id2word[random.choice(res[0])]\n",
    "    for i in range(100):\n",
    "        c = model._id2word[random.choice(res[0])]\n",
    "        print(a,b,c)\n",
    "        model.analogy(a, b, c)\n",
    "\n",
    "#     for i in range(100):\n",
    "#         a = b'russians'\n",
    "#         b = b'vodka'\n",
    "#         c = model._id2word[random.choice(vals[0])]\n",
    "#         print(a,b,c)\n",
    "#         model.analogy(a, b, c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data file:  ./text8\n",
      "Vocab size:  71290  + UNK\n",
      "Words per epoch:  17005207\n",
      "\n",
      "b'zeus'\n",
      "=====================================\n",
      "b'zeus'              1.0000\n",
      "b'hera'              0.7958\n",
      "b'aphrodite'         0.6638\n",
      "b'poseidon'          0.6635\n",
      "b'artemis'           0.6548\n",
      "b'hephaestus'        0.6515\n",
      "b'heracles'          0.6409\n",
      "b'athena'            0.6050\n",
      "b'demeter'           0.5943\n",
      "b'gods'              0.5854\n",
      "b'goddess'           0.5776\n",
      "b'cronus'            0.5631\n",
      "b'hermes'            0.5562\n",
      "b'gigantes'          0.5558\n",
      "b'ares'              0.5557\n",
      "b'eurystheus'        0.5492\n",
      "b'minos'             0.5450\n",
      "b'pasiphae'          0.5371\n",
      "b'arcas'             0.5353\n",
      "b'lycaeus'           0.5327\n",
      "b'coffee' b'drink' b'bargains'\n",
      "b'intercede'\n",
      "b'coffee' b'drink' b'ninhursag'\n",
      "b'enki'\n",
      "b'coffee' b'drink' b'bandinelli'\n",
      "b'bartolommeo'\n",
      "b'coffee' b'drink' b'tantalus'\n",
      "b'matron'\n",
      "b'coffee' b'drink' b'ambrosia'\n",
      "b'thetis'\n",
      "b'coffee' b'drink' b'woman'\n",
      "b'women'\n",
      "b'coffee' b'drink' b'uranus'\n",
      "b'neptune'\n",
      "b'coffee' b'drink' b'yudhishthira'\n",
      "b'masami'\n",
      "b'coffee' b'drink' b'gevarus'\n",
      "b'nanna'\n",
      "b'coffee' b'drink' b'kerenyi'\n",
      "b'myth'\n",
      "b'coffee' b'drink' b'gandalf'\n",
      "b'denethor'\n",
      "b'coffee' b'drink' b'antiochus'\n",
      "b'epiphanes'\n",
      "b'coffee' b'drink' b'observing'\n",
      "b'observed'\n",
      "b'coffee' b'drink' b'cepheus'\n",
      "b'cassiopeia'\n",
      "b'coffee' b'drink' b'bargains'\n",
      "b'intercede'\n",
      "b'coffee' b'drink' b'begged'\n",
      "b'persecute'\n",
      "b'coffee' b'drink' b'admetus'\n",
      "b'pelias'\n",
      "b'coffee' b'drink' b'arcas'\n",
      "b'callisto'\n",
      "b'coffee' b'drink' b'telamon'\n",
      "b'peleus'\n",
      "b'coffee' b'drink' b'incestuous'\n",
      "b'incest'\n",
      "b'coffee' b'drink' b'valentinian'\n",
      "b'christianity'\n",
      "b'coffee' b'drink' b'durga'\n",
      "b'goddess'\n",
      "b'coffee' b'drink' b'aulis'\n",
      "b'yalu'\n",
      "b'coffee' b'drink' b'bedivere'\n",
      "b'strode'\n",
      "b'coffee' b'drink' b'hearth'\n",
      "b'deity'\n",
      "b'coffee' b'drink' b'cleopatra'\n",
      "b'antony'\n",
      "b'coffee' b'drink' b'constellation'\n",
      "b'aquarius'\n",
      "b'coffee' b'drink' b'wife'\n",
      "b'son'\n",
      "b'coffee' b'drink' b'hesiod'\n",
      "b'theogony'\n",
      "b'coffee' b'drink' b'macaria'\n",
      "b'dionysus'\n",
      "b'coffee' b'drink' b'ambrosia'\n",
      "b'thetis'\n",
      "b'coffee' b'drink' b'thor'\n",
      "b'valhalla'\n",
      "b'coffee' b'drink' b'trojan'\n",
      "b'trojans'\n",
      "b'coffee' b'drink' b'antipater'\n",
      "b'lysimachus'\n",
      "b'coffee' b'drink' b'possibly'\n",
      "b'probably'\n",
      "b'coffee' b'drink' b'anahobe'\n",
      "b'iname'\n",
      "b'coffee' b'drink' b'sarpedon'\n",
      "b'rhadamanthys'\n",
      "b'coffee' b'drink' b'ariadne'\n",
      "b'minos'\n",
      "b'coffee' b'drink' b'temples'\n",
      "b'worship'\n",
      "b'coffee' b'drink' b'murderous'\n",
      "b'rampage'\n",
      "b'coffee' b'drink' b'ogdoad'\n",
      "b'deity'\n",
      "b'coffee' b'drink' b'murderous'\n",
      "b'rampage'\n",
      "b'coffee' b'drink' b'niobe'\n",
      "b'amphion'\n",
      "b'coffee' b'drink' b'poseidon'\n",
      "b'zeus'\n",
      "b'coffee' b'drink' b'mithras'\n",
      "b'mithra'\n",
      "b'coffee' b'drink' b'euripides'\n",
      "b'aeschylus'\n",
      "b'coffee' b'drink' b'tegea'\n",
      "b'cronos'\n",
      "b'coffee' b'drink' b'clytemnestra'\n",
      "b'aegisthus'\n",
      "b'coffee' b'drink' b'anahobe'\n",
      "b'iname'\n",
      "b'coffee' b'drink' b'sun'\n",
      "b'moon'\n",
      "b'coffee' b'drink' b'jehoram'\n",
      "b'jehu'\n",
      "b'coffee' b'drink' b'rameses'\n",
      "b'antiochus'\n",
      "b'coffee' b'drink' b'minucius'\n",
      "b'fabius'\n",
      "b'coffee' b'drink' b'menelaus'\n",
      "b'fulk'\n",
      "b'coffee' b'drink' b'hyacinthus'\n",
      "b'hyacinth'\n",
      "b'coffee' b'drink' b'vipsania'\n",
      "b'agrippina'\n",
      "b'coffee' b'drink' b'ctesias'\n",
      "b'cronos'\n",
      "b'coffee' b'drink' b'hecuba'\n",
      "b'andromache'\n",
      "b'coffee' b'drink' b'caterina'\n",
      "b'masami'\n",
      "b'coffee' b'drink' b'ayya'\n",
      "b'vaikundar'\n",
      "b'coffee' b'drink' b'chalcis'\n",
      "b'eligius'\n",
      "b'coffee' b'drink' b'olympian'\n",
      "b'gods'\n",
      "b'coffee' b'drink' b'malaclypse'\n",
      "b'eris'\n",
      "b'coffee' b'drink' b'hathor'\n",
      "b'amun'\n",
      "b'coffee' b'drink' b'melanippe'\n",
      "b'antiope'\n",
      "b'coffee' b'drink' b'yisra'\n",
      "b'tiberian'\n",
      "b'coffee' b'drink' b'aphrodisiac'\n",
      "b'sacrifice'\n",
      "b'coffee' b'drink' b'hyginus'\n",
      "b'ovid'\n",
      "b'coffee' b'drink' b'steals'\n",
      "b'dionysus'\n",
      "b'coffee' b'drink' b'aegisthus'\n",
      "b'clytemnestra'\n",
      "b'coffee' b'drink' b'discord'\n",
      "b'strife'\n",
      "b'coffee' b'drink' b'jealous'\n",
      "b'angry'\n",
      "b'coffee' b'drink' b'cursed'\n",
      "b'god'\n",
      "b'coffee' b'drink' b'uballit'\n",
      "b'mehmed'\n",
      "b'coffee' b'drink' b'ariadne'\n",
      "b'minos'\n",
      "b'coffee' b'drink' b'tiresias'\n",
      "b'heracles'\n",
      "b'coffee' b'drink' b'divinities'\n",
      "b'goddess'\n",
      "b'coffee' b'drink' b'basileus'\n",
      "b'maius'\n",
      "b'coffee' b'drink' b'gylfi'\n",
      "b'unn'\n",
      "b'coffee' b'drink' b'gothicus'\n",
      "b'fausta'\n",
      "b'coffee' b'drink' b'ganymede'\n",
      "b'neptune'\n",
      "b'coffee' b'drink' b'pope'\n",
      "b'archbishop'\n",
      "b'coffee' b'drink' b'inscription'\n",
      "b'inscriptions'\n",
      "b'coffee' b'drink' b'colonists'\n",
      "b'colony'\n",
      "b'coffee' b'drink' b'venerated'\n",
      "b'worshipped'\n",
      "b'coffee' b'drink' b'maia'\n",
      "b'believing'\n",
      "b'coffee' b'drink' b'unn'\n",
      "b'loki'\n",
      "b'coffee' b'drink' b'slay'\n",
      "b'repent'\n",
      "b'coffee' b'drink' b'rhea'\n",
      "b'cronos'\n",
      "b'coffee' b'drink' b'pindar'\n",
      "b'callimachus'\n",
      "b'coffee' b'drink' b'israelites'\n",
      "b'yahweh'\n",
      "b'coffee' b'drink' b'aegeus'\n",
      "b'heracles'\n",
      "b'coffee' b'drink' b'vipsanius'\n",
      "b'caesar'\n",
      "b'coffee' b'drink' b'mut'\n",
      "b'god'\n",
      "b'coffee' b'drink' b'freya'\n",
      "b'odin'\n",
      "b'coffee' b'drink' b'acropolis'\n",
      "b'athens'\n",
      "b'coffee' b'drink' b'ousia'\n",
      "b'god'\n",
      "b'coffee' b'drink' b'theodorus'\n",
      "b'saviour'\n",
      "b'coffee' b'drink' b'titans'\n",
      "b'cronos'\n",
      "b'coffee' b'drink' b'satyrs'\n",
      "b'cronos'\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "temp = []\n",
    "with tf.Graph().as_default(), tf.Session() as session:\n",
    "    model = Word2Vec(opts, session)\n",
    "    model.saver.restore(session, os.path.join(opts.save_path, \"model.ckpt-15092945\"))\n",
    "    vals = model.nearby([b'zeus'])\n",
    "    for i in range(100):\n",
    "        a = b'coffee'\n",
    "        b = b'drink'\n",
    "        c = model._id2word[random.choice(vals[0])]\n",
    "        print(a,b,c)\n",
    "        temp.append(model.analogy(a, b, c))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tranform relations into dataframe and save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "triplets = pd.DataFrame()\n",
    "for x in temp:\n",
    "    df = pd.Series([x[0],'11',x[1]])\n",
    "    triplets = triplets.append(df, ignore_index=True)\n",
    "    with open('saved_triplets.pkl', 'wb') as f:\n",
    "    # Pickle the 'data' dictionary using the highest protocol available.\n",
    "      pickle.dump(triplets, f, pickle.HIGHEST_PROTOCOL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>b'bargains'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'intercede'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b'ninhursag'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'enki'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>b'bandinelli'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'bartolommeo'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b'tantalus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'matron'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>b'ambrosia'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'thetis'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>b'woman'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'women'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>b'uranus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'neptune'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>b'yudhishthira'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'masami'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>b'gevarus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'nanna'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>b'kerenyi'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'myth'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>b'gandalf'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'denethor'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>b'antiochus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'epiphanes'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>b'observing'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'observed'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>b'cepheus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'cassiopeia'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>b'bargains'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'intercede'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>b'begged'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'persecute'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>b'admetus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'pelias'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>b'arcas'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'callisto'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>b'telamon'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'peleus'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>b'incestuous'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'incest'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>b'valentinian'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'christianity'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>b'durga'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'goddess'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>b'aulis'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'yalu'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>b'bedivere'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'strode'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>b'hearth'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'deity'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>b'cleopatra'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'antony'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>b'constellation'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'aquarius'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>b'wife'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'son'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>b'hesiod'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'theogony'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>b'macaria'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'dionysus'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>b'discord'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'strife'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>b'jealous'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'angry'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>b'cursed'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'god'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>b'uballit'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'mehmed'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>b'ariadne'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'minos'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>b'tiresias'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'heracles'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>b'divinities'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'goddess'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>b'basileus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'maius'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>b'gylfi'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'unn'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>b'gothicus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'fausta'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>b'ganymede'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'neptune'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>b'pope'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'archbishop'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>b'inscription'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'inscriptions'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>b'colonists'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'colony'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>b'venerated'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'worshipped'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>b'maia'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'believing'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>b'unn'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'loki'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>b'slay'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'repent'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>b'rhea'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'cronos'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>b'pindar'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'callimachus'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>b'israelites'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'yahweh'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>b'aegeus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'heracles'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>b'vipsanius'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'caesar'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>b'mut'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'god'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>b'freya'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'odin'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>b'acropolis'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'athens'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>b'ousia'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'god'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>b'theodorus'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'saviour'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>b'titans'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'cronos'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>b'satyrs'</td>\n",
       "      <td>11</td>\n",
       "      <td>b'cronos'</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   0   1                2\n",
       "0        b'bargains'  11     b'intercede'\n",
       "1       b'ninhursag'  11          b'enki'\n",
       "2      b'bandinelli'  11   b'bartolommeo'\n",
       "3        b'tantalus'  11        b'matron'\n",
       "4        b'ambrosia'  11        b'thetis'\n",
       "5           b'woman'  11         b'women'\n",
       "6          b'uranus'  11       b'neptune'\n",
       "7    b'yudhishthira'  11        b'masami'\n",
       "8         b'gevarus'  11         b'nanna'\n",
       "9         b'kerenyi'  11          b'myth'\n",
       "10        b'gandalf'  11      b'denethor'\n",
       "11      b'antiochus'  11     b'epiphanes'\n",
       "12      b'observing'  11      b'observed'\n",
       "13        b'cepheus'  11    b'cassiopeia'\n",
       "14       b'bargains'  11     b'intercede'\n",
       "15         b'begged'  11     b'persecute'\n",
       "16        b'admetus'  11        b'pelias'\n",
       "17          b'arcas'  11      b'callisto'\n",
       "18        b'telamon'  11        b'peleus'\n",
       "19     b'incestuous'  11        b'incest'\n",
       "20    b'valentinian'  11  b'christianity'\n",
       "21          b'durga'  11       b'goddess'\n",
       "22          b'aulis'  11          b'yalu'\n",
       "23       b'bedivere'  11        b'strode'\n",
       "24         b'hearth'  11         b'deity'\n",
       "25      b'cleopatra'  11        b'antony'\n",
       "26  b'constellation'  11      b'aquarius'\n",
       "27           b'wife'  11           b'son'\n",
       "28         b'hesiod'  11      b'theogony'\n",
       "29        b'macaria'  11      b'dionysus'\n",
       "..               ...  ..              ...\n",
       "70        b'discord'  11        b'strife'\n",
       "71        b'jealous'  11         b'angry'\n",
       "72         b'cursed'  11           b'god'\n",
       "73        b'uballit'  11        b'mehmed'\n",
       "74        b'ariadne'  11         b'minos'\n",
       "75       b'tiresias'  11      b'heracles'\n",
       "76     b'divinities'  11       b'goddess'\n",
       "77       b'basileus'  11         b'maius'\n",
       "78          b'gylfi'  11           b'unn'\n",
       "79       b'gothicus'  11        b'fausta'\n",
       "80       b'ganymede'  11       b'neptune'\n",
       "81           b'pope'  11    b'archbishop'\n",
       "82    b'inscription'  11  b'inscriptions'\n",
       "83      b'colonists'  11        b'colony'\n",
       "84      b'venerated'  11    b'worshipped'\n",
       "85           b'maia'  11     b'believing'\n",
       "86            b'unn'  11          b'loki'\n",
       "87           b'slay'  11        b'repent'\n",
       "88           b'rhea'  11        b'cronos'\n",
       "89         b'pindar'  11   b'callimachus'\n",
       "90     b'israelites'  11        b'yahweh'\n",
       "91         b'aegeus'  11      b'heracles'\n",
       "92      b'vipsanius'  11        b'caesar'\n",
       "93            b'mut'  11           b'god'\n",
       "94          b'freya'  11          b'odin'\n",
       "95      b'acropolis'  11        b'athens'\n",
       "96          b'ousia'  11           b'god'\n",
       "97      b'theodorus'  11       b'saviour'\n",
       "98         b'titans'  11        b'cronos'\n",
       "99         b'satyrs'  11        b'cronos'\n",
       "\n",
       "[100 rows x 3 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "triplets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({0: 3,\n",
       "         1: 1,\n",
       "         2: 1,\n",
       "         3: 739,\n",
       "         4: 1,\n",
       "         5: 11,\n",
       "         6: 1729,\n",
       "         7: 973,\n",
       "         8: 1,\n",
       "         9: 2369,\n",
       "         10: 807,\n",
       "         11: 2,\n",
       "         12: 5,\n",
       "         13: 1,\n",
       "         14: 1,\n",
       "         15: 495,\n",
       "         16: 718,\n",
       "         17: 561,\n",
       "         18: 1,\n",
       "         19: 2,\n",
       "         20: 1,\n",
       "         21: 578,\n",
       "         22: 1,\n",
       "         23: 2,\n",
       "         24: 1,\n",
       "         25: 624,\n",
       "         26: 1,\n",
       "         27: 1,\n",
       "         28: 1,\n",
       "         29: 1,\n",
       "         30: 1,\n",
       "         31: 1,\n",
       "         32: 1,\n",
       "         33: 729,\n",
       "         34: 1,\n",
       "         35: 3,\n",
       "         36: 1,\n",
       "         37: 1,\n",
       "         38: 4,\n",
       "         39: 610,\n",
       "         40: 1,\n",
       "         41: 1,\n",
       "         42: 1,\n",
       "         43: 1,\n",
       "         44: 406,\n",
       "         45: 1,\n",
       "         46: 855,\n",
       "         47: 2,\n",
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       "         50: 591,\n",
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       "         53: 1,\n",
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       "         61: 1,\n",
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       "         63: 1048,\n",
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       "         66: 558,\n",
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       "         72: 698,\n",
       "         73: 1,\n",
       "         74: 1,\n",
       "         75: 3,\n",
       "         76: 716,\n",
       "         77: 529,\n",
       "         78: 2,\n",
       "         79: 1,\n",
       "         80: 1,\n",
       "         81: 1,\n",
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       "         84: 1,\n",
       "         85: 2,\n",
       "         86: 1,\n",
       "         87: 1,\n",
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       "         93: 572,\n",
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       "         106: 2,\n",
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       "         110: 900,\n",
       "         111: 1,\n",
       "         112: 1,\n",
       "         113: 759,\n",
       "         114: 134,\n",
       "         115: 2,\n",
       "         116: 2,\n",
       "         117: 1,\n",
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       "         120: 1,\n",
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       "         124: 2,\n",
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       "         126: 662,\n",
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       "         129: 1,\n",
       "         130: 2,\n",
       "         131: 1,\n",
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       "         135: 2,\n",
       "         136: 1,\n",
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       "         141: 894,\n",
       "         142: 1,\n",
       "         143: 1,\n",
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       "         147: 565,\n",
       "         148: 1,\n",
       "         149: 911,\n",
       "         150: 791,\n",
       "         151: 943,\n",
       "         152: 3,\n",
       "         153: 2,\n",
       "         154: 424,\n",
       "         155: 669,\n",
       "         156: 1,\n",
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       "         158: 1,\n",
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       "         160: 1,\n",
       "         161: 1,\n",
       "         162: 539,\n",
       "         163: 849,\n",
       "         164: 944,\n",
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       "         168: 1,\n",
       "         169: 3,\n",
       "         170: 856,\n",
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       "         175: 1,\n",
       "         176: 873,\n",
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       "         179: 1,\n",
       "         180: 1,\n",
       "         181: 802,\n",
       "         182: 449,\n",
       "         183: 1,\n",
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       "         185: 1,\n",
       "         186: 1,\n",
       "         187: 3,\n",
       "         188: 1036,\n",
       "         189: 676,\n",
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       "         193: 1,\n",
       "         194: 1,\n",
       "         195: 439,\n",
       "         196: 1,\n",
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       "         199: 1,\n",
       "         200: 1,\n",
       "         201: 1,\n",
       "         202: 652,\n",
       "         203: 812,\n",
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       "         205: 1,\n",
       "         206: 2,\n",
       "         207: 1,\n",
       "         208: 830,\n",
       "         209: 491,\n",
       "         210: 648,\n",
       "         211: 842,\n",
       "         212: 1,\n",
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       "         214: 1,\n",
       "         215: 1,\n",
       "         216: 2,\n",
       "         217: 2,\n",
       "         218: 475,\n",
       "         219: 2,\n",
       "         220: 979,\n",
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       "         222: 3,\n",
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       "         224: 1,\n",
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       "         226: 644,\n",
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       "         231: 1,\n",
       "         232: 606,\n",
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       "         239: 1,\n",
       "         240: 3,\n",
       "         241: 1,\n",
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       "         243: 1,\n",
       "         244: 1,\n",
       "         245: 260,\n",
       "         246: 1,\n",
       "         247: 599,\n",
       "         248: 451,\n",
       "         249: 1211,\n",
       "         250: 1,\n",
       "         251: 1,\n",
       "         252: 699,\n",
       "         253: 1,\n",
       "         254: 1,\n",
       "         255: 792,\n",
       "         256: 1,\n",
       "         257: 1,\n",
       "         258: 3,\n",
       "         259: 1,\n",
       "         260: 848,\n",
       "         261: 1,\n",
       "         262: 1,\n",
       "         263: 667,\n",
       "         264: 1,\n",
       "         265: 1,\n",
       "         266: 1,\n",
       "         267: 964,\n",
       "         268: 419,\n",
       "         269: 1,\n",
       "         270: 1,\n",
       "         271: 1,\n",
       "         272: 2,\n",
       "         273: 2,\n",
       "         274: 1,\n",
       "         275: 2,\n",
       "         276: 1,\n",
       "         277: 1,\n",
       "         278: 609,\n",
       "         279: 3,\n",
       "         280: 1,\n",
       "         281: 1,\n",
       "         282: 1,\n",
       "         283: 842,\n",
       "         284: 762,\n",
       "         285: 691,\n",
       "         286: 1,\n",
       "         287: 2,\n",
       "         288: 2,\n",
       "         289: 1,\n",
       "         290: 1,\n",
       "         291: 1,\n",
       "         292: 1,\n",
       "         293: 1,\n",
       "         294: 1,\n",
       "         295: 2,\n",
       "         296: 1,\n",
       "         297: 1,\n",
       "         298: 1,\n",
       "         299: 1})"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import Counter\n",
    "Counter(assignments)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "res = np.where(assignments==211)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'political'\n",
      "b'economic'\n",
      "b'liberal'\n",
      "b'communist'\n",
      "b'conservative'\n",
      "b'wing'\n",
      "b'governments'\n",
      "b'democracy'\n",
      "b'movements'\n",
      "b'policies'\n",
      "b'revolutionary'\n",
      "b'economics'\n",
      "b'socialist'\n",
      "b'wealth'\n",
      "b'capitalism'\n",
      "b'marx'\n",
      "b'liberty'\n",
      "b'communism'\n",
      "b'unions'\n",
      "b'nationalist'\n",
      "b'communists'\n",
      "b'liberalism'\n",
      "b'liberals'\n",
      "b'economies'\n",
      "b'socialism'\n",
      "b'fascist'\n",
      "b'ideology'\n",
      "b'anarchist'\n",
      "b'capitalist'\n",
      "b'marxist'\n",
      "b'nationalism'\n",
      "b'semitism'\n",
      "b'equality'\n",
      "b'anarchism'\n",
      "b'welfare'\n",
      "b'fascism'\n",
      "b'anarcho'\n",
      "b'libertarian'\n",
      "b'peasants'\n",
      "b'prosperity'\n",
      "b'marxism'\n",
      "b'agenda'\n",
      "b'manifesto'\n",
      "b'dictatorship'\n",
      "b'coercion'\n",
      "b'imperialism'\n",
      "b'anarchists'\n",
      "b'ideological'\n",
      "b'ideals'\n",
      "b'nationalists'\n",
      "b'authoritarian'\n",
      "b'bloc'\n",
      "b'regimes'\n",
      "b'socialists'\n",
      "b'hayek'\n",
      "b'militant'\n",
      "b'racism'\n",
      "b'intellectuals'\n",
      "b'conservatism'\n",
      "b'centralized'\n",
      "b'feudalism'\n",
      "b'bureaucracy'\n",
      "b'racist'\n",
      "b'revolutions'\n",
      "b'dada'\n",
      "b'keynes'\n",
      "b'communal'\n",
      "b'oppression'\n",
      "b'individualist'\n",
      "b'quo'\n",
      "b'patriotic'\n",
      "b'alliances'\n",
      "b'activism'\n",
      "b'democracies'\n",
      "b'radicals'\n",
      "b'islamist'\n",
      "b'solidarity'\n",
      "b'persecuted'\n",
      "b'repression'\n",
      "b'capitalists'\n",
      "b'anarchy'\n",
      "b'zionism'\n",
      "b'aristocracy'\n",
      "b'revolutionaries'\n",
      "b'ethic'\n",
      "b'marxists'\n",
      "b'leftist'\n",
      "b'bourgeois'\n",
      "b'rothbard'\n",
      "b'illuminati'\n",
      "b'ideologies'\n",
      "b'pragmatic'\n",
      "b'socio'\n",
      "b'faire'\n",
      "b'industrialized'\n",
      "b'colonialism'\n",
      "b'totalitarian'\n",
      "b'nazism'\n",
      "b'fundamentalism'\n",
      "b'laissez'\n",
      "b'keynesian'\n",
      "b'whig'\n",
      "b'agrarian'\n",
      "b'guilds'\n",
      "b'pamphlet'\n",
      "b'advocating'\n",
      "b'mercantilism'\n",
      "b'dissent'\n",
      "b'industrialization'\n",
      "b'oppressive'\n",
      "b'reformers'\n",
      "b'globalization'\n",
      "b'opposes'\n",
      "b'neoclassical'\n",
      "b'pacifist'\n",
      "b'leaning'\n",
      "b'fundamentalists'\n",
      "b'alienation'\n",
      "b'populist'\n",
      "b'individualism'\n",
      "b'centrally'\n",
      "b'tyranny'\n",
      "b'criticize'\n",
      "b'bureaucratic'\n",
      "b'proudhon'\n",
      "b'whigs'\n",
      "b'undermine'\n",
      "b'utopian'\n",
      "b'coercive'\n",
      "b'eco'\n",
      "b'utopia'\n",
      "b'libertarianism'\n",
      "b'espoused'\n",
      "b'dictators'\n",
      "b'repressive'\n",
      "b'decentralized'\n",
      "b'libertarians'\n",
      "b'elites'\n",
      "b'liberalization'\n",
      "b'dictatorships'\n",
      "b'stalinist'\n",
      "b'federalism'\n",
      "b'autocratic'\n",
      "b'egalitarian'\n",
      "b'leninist'\n",
      "b'imperialist'\n",
      "b'peasantry'\n",
      "b'reactionary'\n",
      "b'atheistic'\n",
      "b'proletariat'\n",
      "b'sectarian'\n",
      "b'schumpeter'\n",
      "b'leninism'\n",
      "b'corporatism'\n",
      "b'hegemony'\n",
      "b'totalitarianism'\n",
      "b'staunch'\n",
      "b'islamism'\n",
      "b'sympathies'\n",
      "b'environmentalists'\n",
      "b'fostered'\n",
      "b'serfdom'\n",
      "b'bastiat'\n",
      "b'organizer'\n",
      "b'fascists'\n",
      "b'adhered'\n",
      "b'landowners'\n",
      "b'entrepreneurship'\n",
      "b'bakunin'\n",
      "b'nationalistic'\n",
      "b'egalitarianism'\n",
      "b'zinoviev'\n",
      "b'discredit'\n",
      "b'environmentalism'\n",
      "b'hypocrisy'\n",
      "b'extremist'\n",
      "b'macroeconomics'\n",
      "b'jewry'\n",
      "b'dissenters'\n",
      "b'eurosceptic'\n",
      "b'monarchical'\n",
      "b'expressionism'\n",
      "b'bourgeoisie'\n",
      "b'upheaval'\n",
      "b'centralised'\n",
      "b'mercantile'\n",
      "b'anathema'\n",
      "b'intellectualism'\n",
      "b'lofty'\n",
      "b'glasnost'\n",
      "b'nonviolent'\n",
      "b'authoritarianism'\n",
      "b'ideologically'\n",
      "b'collectivism'\n",
      "b'dismantling'\n",
      "b'individualists'\n",
      "b'leftists'\n",
      "b'pacifism'\n",
      "b'leanings'\n",
      "b'absolutism'\n",
      "b'mercantilist'\n",
      "b'statist'\n",
      "b'subsumed'\n",
      "b'purged'\n",
      "b'conciliation'\n",
      "b'inequalities'\n",
      "b'modernize'\n",
      "b'ngos'\n",
      "b'distributism'\n",
      "b'jacobitism'\n",
      "b'socioeconomic'\n",
      "b'stances'\n",
      "b'superpower'\n",
      "b'collectivization'\n",
      "b'dictatorial'\n",
      "b'criticizes'\n",
      "b'maoist'\n",
      "b'fatherland'\n",
      "b'favours'\n",
      "b'disaffected'\n",
      "b'favouring'\n",
      "b'luddites'\n",
      "b'stalinism'\n",
      "b'undermining'\n",
      "b'disadvantaged'\n",
      "b'feuds'\n",
      "b'participatory'\n",
      "b'islamists'\n",
      "b'bureaucrats'\n",
      "b'theocratic'\n",
      "b'ills'\n",
      "b'kropotkin'\n",
      "b'eugenic'\n",
      "b'eurosceptics'\n",
      "b'industrialised'\n",
      "b'syndicalism'\n",
      "b'nationalization'\n",
      "b'slogans'\n",
      "b'secularism'\n",
      "b'antagonism'\n",
      "b'mccarthyism'\n",
      "b'tutelage'\n",
      "b'microeconomic'\n",
      "b'denounce'\n",
      "b'republicanism'\n",
      "b'traditionalist'\n",
      "b'expansionism'\n",
      "b'perpetuated'\n",
      "b'liberating'\n",
      "b'radicalism'\n",
      "b'stressing'\n",
      "b'democide'\n",
      "b'multiculturalism'\n",
      "b'oligarchy'\n",
      "b'gime'\n",
      "b'modernists'\n",
      "b'collectivist'\n",
      "b'monarchists'\n",
      "b'separatism'\n",
      "b'democratization'\n",
      "b'bolshevism'\n",
      "b'lysander'\n",
      "b'industrialists'\n",
      "b'forerunners'\n",
      "b'monarchist'\n",
      "b'deepened'\n",
      "b'organisational'\n",
      "b'protectionism'\n",
      "b'distanced'\n",
      "b'squarely'\n",
      "b'outwardly'\n",
      "b'globalisation'\n",
      "b'furthered'\n",
      "b'citizenry'\n",
      "b'zionists'\n",
      "b'universalists'\n",
      "b'allegiances'\n",
      "b'looser'\n",
      "b'geopolitical'\n",
      "b'transnational'\n",
      "b'meritocracy'\n",
      "b'protectionist'\n",
      "b'appellation'\n",
      "b'elitism'\n",
      "b'qualifier'\n",
      "b'upheavals'\n",
      "b'staunchly'\n",
      "b'jacobin'\n",
      "b'countering'\n",
      "b'wealthier'\n",
      "b'appeasement'\n",
      "b'wingers'\n",
      "b'ltv'\n",
      "b'motherland'\n",
      "b'syndicalist'\n",
      "b'interwar'\n",
      "b'outnumber'\n",
      "b'blaming'\n",
      "b'campaigners'\n",
      "b'autocracy'\n",
      "b'mensheviks'\n",
      "b'classicism'\n",
      "b'agendas'\n",
      "b'emanated'\n",
      "b'neoliberalism'\n",
      "b'interventionist'\n",
      "b'bigotry'\n",
      "b'intolerant'\n",
      "b'ancien'\n",
      "b'persistently'\n",
      "b'mutualism'\n",
      "b'unionism'\n",
      "b'liberalisation'\n",
      "b'perpetuating'\n",
      "b'militarism'\n",
      "b'vestiges'\n",
      "b'euroscepticism'\n",
      "b'legitimize'\n",
      "b'futurism'\n",
      "b'cnt'\n",
      "b'quarrels'\n",
      "b'trotskyist'\n",
      "b'scapegoat'\n",
      "b'heterodox'\n",
      "b'stratification'\n",
      "b'centralization'\n",
      "b'belloc'\n",
      "b'anarchic'\n",
      "b'ruthlessly'\n",
      "b'theocracy'\n",
      "b'philanthropic'\n",
      "b'intelligentsia'\n",
      "b'luddite'\n",
      "b'syndicalists'\n",
      "b'metternich'\n",
      "b'manifestos'\n",
      "b'coexistence'\n",
      "b'trotskyists'\n",
      "b'restrain'\n",
      "b'collectives'\n",
      "b'irredentist'\n",
      "b'connotes'\n",
      "b'unjustified'\n",
      "b'tyrannical'\n",
      "b'zapatista'\n",
      "b'hardline'\n",
      "b'cooperatives'\n",
      "b'expansionist'\n",
      "b'maoism'\n",
      "b'marxian'\n",
      "b'sleepers'\n",
      "b'apolitical'\n",
      "b'marginalized'\n",
      "b'despotism'\n",
      "b'tiered'\n",
      "b'statism'\n",
      "b'formalist'\n",
      "b'distributist'\n",
      "b'clearest'\n",
      "b'corporatist'\n",
      "b'sympathized'\n",
      "b'overman'\n",
      "b'adepts'\n",
      "b'msi'\n",
      "b'ecologists'\n",
      "b'averse'\n",
      "b'ushering'\n",
      "b'disputing'\n",
      "b'trotskyism'\n",
      "b'bastion'\n",
      "b'reconstructionism'\n",
      "b'proliferated'\n",
      "b'meritocratic'\n",
      "b'keynesianism'\n",
      "b'xers'\n",
      "b'undercut'\n",
      "b'mercantilists'\n",
      "b'betraying'\n",
      "b'harmonize'\n",
      "b'minarchists'\n",
      "b'blossomed'\n",
      "b'championing'\n",
      "b'crony'\n",
      "b'thatcherism'\n",
      "b'unworkable'\n",
      "b'hegelians'\n",
      "b'resent'\n",
      "b'technocracy'\n",
      "b'glorifying'\n",
      "b'unfriendly'\n",
      "b'subordination'\n",
      "b'progressivism'\n",
      "b'unfettered'\n",
      "b'primitivism'\n",
      "b'monetarism'\n",
      "b'autocrat'\n",
      "b'lumped'\n",
      "b'aspired'\n",
      "b'syndicates'\n",
      "b'denounces'\n",
      "b'godless'\n",
      "b'irreconcilable'\n",
      "b'leans'\n",
      "b'rapprochement'\n",
      "b'precondition'\n",
      "b'semite'\n",
      "b'democratisation'\n",
      "b'proletarian'\n",
      "b'falsehoods'\n",
      "b'disenfranchised'\n",
      "b'absolutist'\n",
      "b'keynesians'\n",
      "b'pluralist'\n",
      "b'downplayed'\n",
      "b'interventionism'\n",
      "b'imperatives'\n",
      "b'plekhanov'\n",
      "b'neoliberal'\n",
      "b'empowerment'\n",
      "b'adamantly'\n",
      "b'interdependence'\n",
      "b'politico'\n",
      "b'ostracism'\n",
      "b'benefiting'\n",
      "b'servile'\n",
      "b'finlandization'\n",
      "b'disparage'\n",
      "b'pretensions'\n",
      "b'revisionists'\n",
      "b'criticises'\n",
      "b'internationalist'\n",
      "b'insufficiently'\n",
      "b'isolationist'\n",
      "b'injustices'\n",
      "b'destabilize'\n",
      "b'martov'\n",
      "b'embodying'\n",
      "b'mcelroy'\n",
      "b'neorealism'\n",
      "b'toppling'\n",
      "b'iww'\n",
      "b'segregationist'\n",
      "b'malatesta'\n",
      "b'dissuade'\n",
      "b'ethnocentric'\n",
      "b'meddling'\n",
      "b'expropriation'\n",
      "b'disunity'\n",
      "b'bulwark'\n",
      "b'elitist'\n",
      "b'asatru'\n",
      "b'collectivisation'\n",
      "b'inexorably'\n",
      "b'wholeheartedly'\n",
      "b'monetarist'\n",
      "b'stifle'\n",
      "b'ricardian'\n",
      "b'espouse'\n",
      "b'espouses'\n",
      "b'revolutionize'\n",
      "b'capitalistic'\n",
      "b'pluralistic'\n",
      "b'altruists'\n",
      "b'superseding'\n",
      "b'leaderships'\n",
      "b'genocides'\n",
      "b'austrofascism'\n",
      "b'affluence'\n",
      "b'placate'\n",
      "b'satyagraha'\n",
      "b'estrangement'\n",
      "b'anarcha'\n",
      "b'reshaping'\n",
      "b'vociferous'\n",
      "b'westernized'\n",
      "b'kondratiev'\n",
      "b'nepotism'\n",
      "b'ideologue'\n",
      "b'coexisted'\n",
      "b'heaped'\n",
      "b'discriminating'\n",
      "b'antebellum'\n",
      "b'repudiate'\n",
      "b'unencumbered'\n",
      "b'bureaucracies'\n",
      "b'constitutionalism'\n",
      "b'comecon'\n",
      "b'extremism'\n",
      "b'abolishment'\n",
      "b'neoclassicism'\n",
      "b'intercommunal'\n",
      "b'indoctrination'\n",
      "b'rationalisation'\n",
      "b'takeovers'\n",
      "b'proviso'\n",
      "b'puritanism'\n",
      "b'jeffersonian'\n",
      "b'reorganizing'\n",
      "b'principled'\n",
      "b'bax'\n",
      "b'abhorrent'\n",
      "b'usurpation'\n",
      "b'espousing'\n",
      "b'intergovernmentalism'\n",
      "b'masculist'\n",
      "b'antithetical'\n",
      "b'incipient'\n",
      "b'perpetuation'\n",
      "b'liberalize'\n",
      "b'satirize'\n",
      "b'respectability'\n",
      "b'antiwar'\n",
      "b'commercialism'\n",
      "b'isolationism'\n",
      "b'internationalism'\n",
      "b'bolshevist'\n",
      "b'friendliness'\n",
      "b'novarum'\n",
      "b'haudenosaunee'\n",
      "b'plutocracy'\n",
      "b'neoconservative'\n",
      "b'nonaggression'\n",
      "b'diametrically'\n",
      "b'disestablishment'\n",
      "b'levellers'\n",
      "b'socialized'\n",
      "b'vivisection'\n",
      "b'discrediting'\n",
      "b'blavatsky'\n",
      "b'retort'\n",
      "b'agrarianism'\n",
      "b'hutchins'\n",
      "b'backwardness'\n",
      "b'technocrats'\n",
      "b'irrevocably'\n",
      "b'progressives'\n",
      "b'eradicating'\n",
      "b'supranationalism'\n",
      "b'stifled'\n",
      "b'regrettable'\n",
      "b'headway'\n",
      "b'ostpolitik'\n",
      "b'megali'\n",
      "b'gaians'\n",
      "b'cliques'\n",
      "b'aspires'\n",
      "b'denigrating'\n",
      "b'anarchistic'\n",
      "b'proletarians'\n",
      "b'crudely'\n",
      "b'oppressors'\n",
      "b'withered'\n",
      "b'countercultural'\n",
      "b'leftism'\n",
      "b'channelled'\n",
      "b'physiocrats'\n",
      "b'maoists'\n",
      "b'agitating'\n",
      "b'nihilist'\n",
      "b'moralistic'\n",
      "b'superlatives'\n",
      "b'oligarchic'\n",
      "b'unbridled'\n",
      "b'deniers'\n",
      "b'neoconservatism'\n",
      "b'sectarianism'\n",
      "b'abrogation'\n",
      "b'anticommunist'\n",
      "b'reawakened'\n",
      "b'gradualism'\n",
      "b'eschews'\n",
      "b'ineffectiveness'\n",
      "b'subcultural'\n",
      "b'repressing'\n",
      "b'reemergence'\n",
      "b'mobilizing'\n",
      "b'pnv'\n",
      "b'monopolist'\n",
      "b'culminate'\n",
      "b'subterfuge'\n",
      "b'autonomist'\n",
      "b'maximizes'\n",
      "b'amass'\n",
      "b'realpolitik'\n",
      "b'cartels'\n",
      "b'ohlin'\n",
      "b'inheritors'\n",
      "b'collectivized'\n",
      "b'revivalist'\n",
      "b'proudest'\n",
      "b'paternalistic'\n",
      "b'entanglements'\n",
      "b'disagreeable'\n",
      "b'magisterial'\n",
      "b'centralisation'\n",
      "b'illiberal'\n",
      "b'thwarting'\n",
      "b'myriads'\n",
      "b'jacksonian'\n",
      "b'echelons'\n",
      "b'poum'\n",
      "b'colonialist'\n",
      "b'pasts'\n",
      "b'evocation'\n",
      "b'unattainable'\n",
      "b'literati'\n",
      "b'christadelphian'\n",
      "b'liberalizing'\n",
      "b'jihadist'\n",
      "b'enriching'\n",
      "b'abrogate'\n",
      "b'marginalize'\n",
      "b'regionalism'\n",
      "b'manorialism'\n",
      "b'micronational'\n",
      "b'propagandistic'\n",
      "b'betterment'\n",
      "b'socialistic'\n",
      "b'militancy'\n",
      "b'modicum'\n",
      "b'regicides'\n",
      "b'diluting'\n",
      "b'harmoniously'\n",
      "b'embargoes'\n",
      "b'francoist'\n",
      "b'politicized'\n",
      "b'populism'\n",
      "b'curbing'\n",
      "b'minarchist'\n",
      "b'gravitated'\n",
      "b'avowedly'\n",
      "b'spartacist'\n",
      "b'deflationary'\n",
      "b'imperialists'\n",
      "b'repress'\n",
      "b'hamiltonians'\n",
      "b'arabism'\n",
      "b'coalesce'\n",
      "b'radicalization'\n",
      "b'nihilists'\n",
      "b'communitarian'\n",
      "b'dogmatism'\n",
      "b'normalisation'\n",
      "b'dadaists'\n",
      "b'regimentation'\n",
      "b'objectivists'\n",
      "b'corporative'\n",
      "b'withering'\n",
      "b'middlemen'\n",
      "b'saur'\n",
      "b'factionalism'\n",
      "b'lutton'\n",
      "b'aestheticism'\n",
      "b'reinvigorated'\n",
      "b'balkanization'\n",
      "b'juche'\n",
      "b'insurrectionary'\n",
      "b'swaraj'\n",
      "b'religous'\n",
      "b'communistic'\n",
      "b'abolitionism'\n",
      "b'seperatist'\n",
      "b'freemasonic'\n",
      "b'paternalism'\n",
      "b'herstory'\n",
      "b'typify'\n",
      "b'falange'\n",
      "b'soros'\n",
      "b'centralist'\n",
      "b'anl'\n",
      "b'kernot'\n",
      "b'cgt'\n",
      "b'diplomatically'\n",
      "b'rectitude'\n",
      "b'profiteering'\n",
      "b'ggr'\n",
      "b'westernization'\n",
      "b'neocolonialism'\n",
      "b'imperialistic'\n",
      "b'minarchism'\n",
      "b'colonials'\n",
      "b'eurocentrism'\n",
      "b'thatcherite'\n",
      "b'worldliness'\n",
      "b'stauber'\n",
      "b'majoritarianism'\n",
      "b'legitimizing'\n",
      "b'stridently'\n",
      "b'unease'\n",
      "b'interbellum'\n",
      "b'terrorize'\n",
      "b'moderns'\n",
      "b'corporatocracy'\n",
      "b'combatted'\n",
      "b'collaborationist'\n",
      "b'burkean'\n",
      "b'zollverein'\n",
      "b'agitators'\n",
      "b'klans'\n",
      "b'deobandi'\n",
      "b'exclusionary'\n",
      "b'periodization'\n",
      "b'balasingham'\n",
      "b'fiscally'\n",
      "b'nonconformists'\n",
      "b'bookchin'\n",
      "b'darwinists'\n",
      "b'shortlived'\n",
      "b'matriarchy'\n",
      "b'quickened'\n",
      "b'reevaluate'\n",
      "b'girondins'\n",
      "b'ensconced'\n",
      "b'disinterest'\n",
      "b'utopianism'\n",
      "b'pacifistic'\n",
      "b'mollified'\n",
      "b'autarky'\n",
      "b'quash'\n",
      "b'empt'\n",
      "b'stagnating'\n",
      "b'brandished'\n",
      "b'vindicate'\n",
      "b'reemerged'\n",
      "b'seigneurial'\n",
      "b'trilateral'\n",
      "b'lysenkoism'\n",
      "b'kulturkampf'\n",
      "b'inventiveness'\n",
      "b'kaminer'\n",
      "b'encroachments'\n",
      "b'collectivists'\n",
      "b'utilitarians'\n",
      "b'decentralised'\n",
      "b'interrelations'\n",
      "b'workingmen'\n",
      "b'cliffe'\n",
      "b'religionists'\n",
      "b'dented'\n",
      "b'usurping'\n",
      "b'stirrings'\n",
      "b'cafiero'\n",
      "b'exceptionalism'\n",
      "b'unfavorably'\n",
      "b'unquestioning'\n",
      "b'bellicose'\n",
      "b'mier'\n",
      "b'warlordism'\n",
      "b'cedars'\n",
      "b'kautsky'\n",
      "b'culottes'\n",
      "b'oligarchical'\n",
      "b'methodically'\n",
      "b'tolerating'\n",
      "b'cosmopolitanism'\n",
      "b'buzzsaw'\n",
      "b'homogenization'\n",
      "b'divestment'\n",
      "b'demonization'\n",
      "b'disassociating'\n",
      "b'superstate'\n",
      "b'clasp'\n",
      "b'premodern'\n",
      "b'anglosphere'\n",
      "b'debatably'\n",
      "b'envisions'\n",
      "b'supremacism'\n",
      "b'crackdowns'\n",
      "b'independency'\n",
      "b'cohesiveness'\n",
      "b'inequities'\n",
      "b'lawmaker'\n",
      "b'landowning'\n",
      "b'disowning'\n",
      "b'underclass'\n",
      "b'apparatchiks'\n",
      "b'rebut'\n",
      "b'refashioned'\n",
      "b'dejacque'\n",
      "b'adherants'\n",
      "b'bulwarks'\n",
      "b'distributists'\n",
      "b'ultranationalist'\n",
      "b'industrialism'\n",
      "b'instigators'\n",
      "b'corporativism'\n",
      "b'counterrevolutionaries'\n",
      "b'urbanism'\n",
      "b'reinvigorate'\n",
      "b'sadao'\n",
      "b'defusing'\n",
      "b'megachurches'\n",
      "b'dehumanized'\n",
      "b'tycoons'\n",
      "b'veers'\n",
      "b'industrialize'\n",
      "b'cleisthenes'\n",
      "b'democratize'\n",
      "b'globalists'\n",
      "b'nots'\n",
      "b'jacobinism'\n",
      "b'inflame'\n",
      "b'proclivities'\n",
      "b'cynically'\n",
      "b'pelerin'\n",
      "b'reactionaries'\n",
      "b'authoritatively'\n",
      "b'sceptic'\n",
      "b'foment'\n",
      "b'scrapping'\n",
      "b'federazione'\n",
      "b'suvorin'\n",
      "b'squatter'\n",
      "b'autocracies'\n",
      "b'candlemakers'\n",
      "b'fascistic'\n",
      "b'mobilisation'\n",
      "b'shirk'\n",
      "b'bureaucratization'\n",
      "b'manoeuvred'\n",
      "b'dystopias'\n",
      "b'vying'\n",
      "b'situationist'\n",
      "b'africanism'\n",
      "b'betrayals'\n",
      "b'propertyless'\n",
      "b'lemkin'\n",
      "b'heresiological'\n",
      "b'actualized'\n",
      "b'inculcated'\n",
      "b'eurocommunism'\n",
      "b'denigrate'\n",
      "b'pilz'\n",
      "b'oligarchs'\n",
      "b'communitarianism'\n",
      "b'cronyism'\n",
      "b'baathist'\n",
      "b'eumc'\n",
      "b'irredenta'\n",
      "b'attac'\n",
      "b'stalinists'\n",
      "b'ardently'\n"
     ]
    }
   ],
   "source": [
    "for s in model._id2word[res]:\n",
    "    print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "res = np.where(assignments==208)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'beer'\n",
      "b'cuisine'\n",
      "b'meat'\n",
      "b'rice'\n",
      "b'milk'\n",
      "b'sugar'\n",
      "b'wine'\n",
      "b'drink'\n",
      "b'coffee'\n",
      "b'fresh'\n",
      "b'tea'\n",
      "b'sweet'\n",
      "b'foods'\n",
      "b'bread'\n",
      "b'cheese'\n",
      "b'honey'\n",
      "b'corn'\n",
      "b'vegetables'\n",
      "b'cooking'\n",
      "b'restaurants'\n",
      "b'chocolate'\n",
      "b'alcoholic'\n",
      "b'dishes'\n",
      "b'cream'\n",
      "b'wheat'\n",
      "b'chicken'\n",
      "b'dish'\n",
      "b'ingredients'\n",
      "b'eaten'\n",
      "b'drinks'\n",
      "b'beans'\n",
      "b'beverages'\n",
      "b'soup'\n",
      "b'meal'\n",
      "b'dairy'\n",
      "b'grains'\n",
      "b'beef'\n",
      "b'flavor'\n",
      "b'maize'\n",
      "b'dried'\n",
      "b'fermentation'\n",
      "b'ham'\n",
      "b'yeast'\n",
      "b'potatoes'\n",
      "b'vegetable'\n",
      "b'fried'\n",
      "b'juice'\n",
      "b'gin'\n",
      "b'sauce'\n",
      "b'recipes'\n",
      "b'cider'\n",
      "b'spam'\n",
      "b'beers'\n",
      "b'cocoa'\n",
      "b'pork'\n",
      "b'bean'\n",
      "b'pepper'\n",
      "b'potato'\n",
      "b'rum'\n",
      "b'curry'\n",
      "b'vegetarian'\n",
      "b'fries'\n",
      "b'ale'\n",
      "b'mushrooms'\n",
      "b'barley'\n",
      "b'beverage'\n",
      "b'spices'\n",
      "b'cheeses'\n",
      "b'cooked'\n",
      "b'pie'\n",
      "b'banana'\n",
      "b'kosher'\n",
      "b'butter'\n",
      "b'brewery'\n",
      "b'fermented'\n",
      "b'staple'\n",
      "b'flour'\n",
      "b'oils'\n",
      "b'brewing'\n",
      "b'meals'\n",
      "b'lime'\n",
      "b'lager'\n",
      "b'breakfast'\n",
      "b'recipe'\n",
      "b'hops'\n",
      "b'lamb'\n",
      "b'nuts'\n",
      "b'shrimp'\n",
      "b'distilled'\n",
      "b'apples'\n",
      "b'syrup'\n",
      "b'ingredient'\n",
      "b'boiled'\n",
      "b'pizza'\n",
      "b'flavour'\n",
      "b'cured'\n",
      "b'liquor'\n",
      "b'bourbon'\n",
      "b'rye'\n",
      "b'ginger'\n",
      "b'poultry'\n",
      "b'soda'\n",
      "b'paste'\n",
      "b'sandwich'\n",
      "b'wines'\n",
      "b'cocktail'\n",
      "b'gelatin'\n",
      "b'cake'\n",
      "b'cuisines'\n",
      "b'stout'\n",
      "b'salad'\n",
      "b'jelly'\n",
      "b'flavors'\n",
      "b'culinary'\n",
      "b'tomatoes'\n",
      "b'hashish'\n",
      "b'cereal'\n",
      "b'mash'\n",
      "b'gallon'\n",
      "b'seafood'\n",
      "b'cajun'\n",
      "b'cereals'\n",
      "b'durian'\n",
      "b'onion'\n",
      "b'malt'\n",
      "b'haggis'\n",
      "b'vinegar'\n",
      "b'flavored'\n",
      "b'blended'\n",
      "b'garlic'\n",
      "b'aroma'\n",
      "b'sesame'\n",
      "b'sour'\n",
      "b'couscous'\n",
      "b'wort'\n",
      "b'peanuts'\n",
      "b'miso'\n",
      "b'stuffed'\n",
      "b'baked'\n",
      "b'cocktails'\n",
      "b'pasta'\n",
      "b'baking'\n",
      "b'thinly'\n",
      "b'smoked'\n",
      "b'whisky'\n",
      "b'cheddar'\n",
      "b'spicy'\n",
      "b'tomato'\n",
      "b'breweries'\n",
      "b'soy'\n",
      "b'spaghetti'\n",
      "b'coconut'\n",
      "b'additives'\n",
      "b'litres'\n",
      "b'vegetarians'\n",
      "b'marmite'\n",
      "b'brewed'\n",
      "b'millet'\n",
      "b'whiskey'\n",
      "b'milder'\n",
      "b'boil'\n",
      "b'vanilla'\n",
      "b'onions'\n",
      "b'peppers'\n",
      "b'vat'\n",
      "b'spoon'\n",
      "b'draught'\n",
      "b'kernels'\n",
      "b'pudding'\n",
      "b'agar'\n",
      "b'pearls'\n",
      "b'irn'\n",
      "b'meats'\n",
      "b'dessert'\n",
      "b'cubes'\n",
      "b'salty'\n",
      "b'canned'\n",
      "b'sausage'\n",
      "b'noodles'\n",
      "b'ales'\n",
      "b'soaked'\n",
      "b'chili'\n",
      "b'desserts'\n",
      "b'cookbook'\n",
      "b'curing'\n",
      "b'stew'\n",
      "b'coco'\n",
      "b'chefs'\n",
      "b'fudge'\n",
      "b'cabbage'\n",
      "b'cakes'\n",
      "b'chop'\n",
      "b'brine'\n",
      "b'ounces'\n",
      "b'fermenting'\n",
      "b'vodka'\n",
      "b'peanut'\n",
      "b'bock'\n",
      "b'noodle'\n",
      "b'scotch'\n",
      "b'steamed'\n",
      "b'seasoned'\n",
      "b'mustard'\n",
      "b'sliced'\n",
      "b'chopped'\n",
      "b'sweetness'\n",
      "b'topping'\n",
      "b'frying'\n",
      "b'flask'\n",
      "b'shellfish'\n",
      "b'whipped'\n",
      "b'drinkers'\n",
      "b'cloudy'\n",
      "b'broth'\n",
      "b'liqueur'\n",
      "b'soybeans'\n",
      "b'squash'\n",
      "b'umami'\n",
      "b'cask'\n",
      "b'flavours'\n",
      "b'grilled'\n",
      "b'carbonated'\n",
      "b'crackers'\n",
      "b'roasted'\n",
      "b'liqueurs'\n",
      "b'crisp'\n",
      "b'dough'\n",
      "b'celery'\n",
      "b'biscuits'\n",
      "b'oats'\n",
      "b'tapioca'\n",
      "b'brandy'\n",
      "b'blends'\n",
      "b'keg'\n",
      "b'peas'\n",
      "b'tasting'\n",
      "b'barb'\n",
      "b'biscuit'\n",
      "b'abv'\n",
      "b'pastry'\n",
      "b'merlot'\n",
      "b'flavoured'\n",
      "b'olives'\n",
      "b'gluten'\n",
      "b'watery'\n",
      "b'broccoli'\n",
      "b'infused'\n",
      "b'sweets'\n",
      "b'custard'\n",
      "b'bottled'\n",
      "b'seaweed'\n",
      "b'lagers'\n",
      "b'sorghum'\n",
      "b'pint'\n",
      "b'mozzarella'\n",
      "b'dipped'\n",
      "b'pumpkin'\n",
      "b'sparkling'\n",
      "b'cassava'\n",
      "b'bun'\n",
      "b'soups'\n",
      "b'steak'\n",
      "b'sausages'\n",
      "b'mashing'\n",
      "b'gravy'\n",
      "b'figs'\n",
      "b'juices'\n",
      "b'sauces'\n",
      "b'salted'\n",
      "b'curd'\n",
      "b'pies'\n",
      "b'moxie'\n",
      "b'softened'\n",
      "b'macaroni'\n",
      "b'minestrone'\n",
      "b'grits'\n",
      "b'sherry'\n",
      "b'roast'\n",
      "b'loaf'\n",
      "b'delicious'\n",
      "b'beets'\n",
      "b'tofu'\n",
      "b'lettuce'\n",
      "b'rennet'\n",
      "b'mutton'\n",
      "b'snack'\n",
      "b'mayonnaise'\n",
      "b'sprinkled'\n",
      "b'freshness'\n",
      "b'manure'\n",
      "b'curries'\n",
      "b'sweetener'\n",
      "b'yum'\n",
      "b'milled'\n",
      "b'pickles'\n",
      "b'dispense'\n",
      "b'distillery'\n",
      "b'doughnut'\n",
      "b'bland'\n",
      "b'wordplay'\n",
      "b'sweetened'\n",
      "b'grill'\n",
      "b'hogs'\n",
      "b'hams'\n",
      "b'oysters'\n",
      "b'sushi'\n",
      "b'argentines'\n",
      "b'lard'\n",
      "b'pasteurization'\n",
      "b'raspberry'\n",
      "b'sandwiches'\n",
      "b'luncheon'\n",
      "b'husk'\n",
      "b'sweeter'\n",
      "b'speciality'\n",
      "b'smelling'\n",
      "b'stale'\n",
      "b'bundaberg'\n",
      "b'barbecue'\n",
      "b'carrots'\n",
      "b'porridge'\n",
      "b'cooks'\n",
      "b'slices'\n",
      "b'pickle'\n",
      "b'pilsner'\n",
      "b'iced'\n",
      "b'yogurt'\n",
      "b'snacks'\n",
      "b'pungent'\n",
      "b'yam'\n",
      "b'gourmet'\n",
      "b'chianti'\n",
      "b'sweeteners'\n",
      "b'ferment'\n",
      "b'pickled'\n",
      "b'oily'\n",
      "b'chilled'\n",
      "b'cayenne'\n",
      "b'seasoning'\n",
      "b'chiuchow'\n",
      "b'brews'\n",
      "b'cucumber'\n",
      "b'eggplant'\n",
      "b'soaking'\n",
      "b'pans'\n",
      "b'mussels'\n",
      "b'ketchup'\n",
      "b'pancake'\n",
      "b'hamburgers'\n",
      "b'soybean'\n",
      "b'mashed'\n",
      "b'malted'\n",
      "b'americanized'\n",
      "b'entr'\n",
      "b'distilling'\n",
      "b'dipping'\n",
      "b'mango'\n",
      "b'flavoring'\n",
      "b'batches'\n",
      "b'mojito'\n",
      "b'pears'\n",
      "b'flavouring'\n",
      "b'skimmed'\n",
      "b'latte'\n",
      "b'masala'\n",
      "b'vegans'\n",
      "b'pints'\n",
      "b'rind'\n",
      "b'teas'\n",
      "b'lye'\n",
      "b'pickling'\n",
      "b'anchovies'\n",
      "b'dill'\n",
      "b'infusions'\n",
      "b'dumplings'\n",
      "b'curds'\n",
      "b'cheesemaking'\n",
      "b'juicy'\n",
      "b'scrambled'\n",
      "b'mex'\n",
      "b'gazpacho'\n",
      "b'flavorings'\n",
      "b'tasty'\n",
      "b'refreshing'\n",
      "b'fruity'\n",
      "b'stuffing'\n",
      "b'doppelbock'\n",
      "b'decoction'\n",
      "b'kimchi'\n",
      "b'strawberries'\n",
      "b'chocolates'\n",
      "b'filo'\n",
      "b'marmalade'\n",
      "b'adulterated'\n",
      "b'pane'\n",
      "b'malts'\n",
      "b'irradiated'\n",
      "b'pounded'\n",
      "b'yolk'\n",
      "b'popcorn'\n",
      "b'cidre'\n",
      "b'unfiltered'\n",
      "b'potted'\n",
      "b'stewed'\n",
      "b'vermouth'\n",
      "b'cob'\n",
      "b'stews'\n",
      "b'leftover'\n",
      "b'odors'\n",
      "b'whey'\n",
      "b'beet'\n",
      "b'tequila'\n",
      "b'drills'\n",
      "b'roasting'\n",
      "b'syrups'\n",
      "b'toothpaste'\n",
      "b'emulsions'\n",
      "b'swede'\n",
      "b'salting'\n",
      "b'mousse'\n",
      "b'pancakes'\n",
      "b'curdled'\n",
      "b'leche'\n",
      "b'sauerkraut'\n",
      "b'hominy'\n",
      "b'hoo'\n",
      "b'kitchens'\n",
      "b'ripened'\n",
      "b'spinach'\n",
      "b'sanitarium'\n",
      "b'cherries'\n",
      "b'gumbo'\n",
      "b'buns'\n",
      "b'bitters'\n",
      "b'thickly'\n",
      "b'tart'\n",
      "b'lentils'\n",
      "b'novelties'\n",
      "b'lautering'\n",
      "b'grist'\n",
      "b'tallow'\n",
      "b'cookbooks'\n",
      "b'earthy'\n",
      "b'cookery'\n",
      "b'buckets'\n",
      "b'bittering'\n",
      "b'chilli'\n",
      "b'molasses'\n",
      "b'halal'\n",
      "b'taro'\n",
      "b'breads'\n",
      "b'grapefruit'\n",
      "b'toppings'\n",
      "b'frites'\n",
      "b'salads'\n",
      "b'julmust'\n",
      "b'bake'\n",
      "b'preservatives'\n",
      "b'greasy'\n",
      "b'hogshead'\n",
      "b'pwnage'\n",
      "b'buckwheat'\n",
      "b'pectin'\n",
      "b'delicacies'\n",
      "b'towels'\n",
      "b'botanicals'\n",
      "b'sprouts'\n",
      "b'turpentine'\n",
      "b'lemonade'\n",
      "b'empanadas'\n",
      "b'kumquats'\n",
      "b'watermelon'\n",
      "b'spoiling'\n",
      "b'pita'\n",
      "b'toasting'\n",
      "b'hopped'\n",
      "b'kvass'\n",
      "b'lemons'\n",
      "b'bittersweet'\n",
      "b'linseed'\n",
      "b'conch'\n",
      "b'turnips'\n",
      "b'yams'\n",
      "b'creamy'\n",
      "b'puppies'\n",
      "b'nutritious'\n",
      "b'skim'\n",
      "b'margarine'\n",
      "b'injera'\n",
      "b'hallertau'\n",
      "b'michelob'\n",
      "b'mung'\n",
      "b'ghee'\n",
      "b'crumbs'\n",
      "b'dumpling'\n",
      "b'monosodium'\n",
      "b'savoury'\n",
      "b'espagnole'\n",
      "b'glycemic'\n",
      "b'carbonation'\n",
      "b'soak'\n",
      "b'simmered'\n",
      "b'thickened'\n",
      "b'minced'\n",
      "b'soba'\n",
      "b'aromas'\n",
      "b'maggots'\n",
      "b'menthol'\n",
      "b'maibock'\n",
      "b'crispy'\n",
      "b'shredded'\n",
      "b'confectionery'\n",
      "b'doughnuts'\n",
      "b'jell'\n",
      "b'spiced'\n",
      "b'prosciutto'\n",
      "b'cucumbers'\n",
      "b'carne'\n",
      "b'vats'\n",
      "b'offal'\n",
      "b'veal'\n",
      "b'liquors'\n",
      "b'oilseed'\n",
      "b'savory'\n",
      "b'brie'\n",
      "b'espresso'\n",
      "b'chestnuts'\n",
      "b'foodstuff'\n",
      "b'emulsifiers'\n",
      "b'concoction'\n",
      "b'ramen'\n",
      "b'canola'\n",
      "b'diners'\n",
      "b'condiments'\n",
      "b'teaspoon'\n",
      "b'banchan'\n",
      "b'bocks'\n",
      "b'bunnies'\n",
      "b'raisins'\n",
      "b'fermentable'\n",
      "b'breaded'\n",
      "b'glutinous'\n",
      "b'corned'\n",
      "b'chiles'\n",
      "b'beeswax'\n",
      "b'normand'\n",
      "b'flirt'\n",
      "b'creams'\n",
      "b'nubcake'\n",
      "b'bladders'\n",
      "b'besan'\n",
      "b'gastronomy'\n",
      "b'acrylics'\n",
      "b'walnuts'\n",
      "b'jambalaya'\n",
      "b'cauliflower'\n",
      "b'cubed'\n",
      "b'pastries'\n",
      "b'plums'\n",
      "b'milanesa'\n",
      "b'tyramine'\n",
      "b'hearty'\n",
      "b'pecan'\n",
      "b'crawfish'\n",
      "b'conching'\n",
      "b'manioc'\n",
      "b'apricot'\n",
      "b'radish'\n",
      "b'straws'\n",
      "b'tortilla'\n",
      "b'steaks'\n",
      "b'bruise'\n",
      "b'crisps'\n",
      "b'garnish'\n",
      "b'tartar'\n",
      "b'cashew'\n",
      "b'unfermented'\n",
      "b'tripe'\n",
      "b'gimlet'\n",
      "b'perfumed'\n",
      "b'tikka'\n",
      "b'dashi'\n",
      "b'fil'\n",
      "b'peeling'\n",
      "b'astringent'\n",
      "b'pasteurized'\n",
      "b'simmering'\n",
      "b'nutritionists'\n",
      "b'dishwasher'\n",
      "b'shrimps'\n",
      "b'goldings'\n",
      "b'unpalatable'\n",
      "b'peppered'\n",
      "b'prawns'\n",
      "b'starchy'\n",
      "b'pomace'\n",
      "b'curdling'\n",
      "b'coarsely'\n",
      "b'unrefined'\n",
      "b'alcopops'\n",
      "b'apricots'\n",
      "b'leaven'\n",
      "b'casks'\n",
      "b'helles'\n",
      "b'earthenware'\n",
      "b'freezer'\n",
      "b'tasted'\n",
      "b'crusts'\n",
      "b'bartenders'\n",
      "b'chunky'\n",
      "b'marinated'\n",
      "b'saut'\n",
      "b'jellies'\n",
      "b'pilsners'\n",
      "b'lagering'\n",
      "b'omelette'\n",
      "b'scrumpy'\n",
      "b'thermos'\n",
      "b'daiquiri'\n",
      "b'semolina'\n",
      "b'husks'\n",
      "b'kneaded'\n",
      "b'barbecued'\n",
      "b'nettle'\n",
      "b'burgers'\n",
      "b'tempura'\n",
      "b'poached'\n",
      "b'perfumes'\n",
      "b'rapeseed'\n",
      "b'zucchini'\n",
      "b'seasonings'\n",
      "b'mochi'\n",
      "b'binders'\n",
      "b'gingerbread'\n",
      "b'szechuan'\n",
      "b'siu'\n",
      "b'marzipan'\n",
      "b'doenjang'\n",
      "b'putrefaction'\n",
      "b'toasted'\n",
      "b'scoops'\n",
      "b'boba'\n",
      "b'gochujang'\n",
      "b'cellophane'\n",
      "b'phenolic'\n",
      "b'udon'\n",
      "b'scented'\n",
      "b'fondue'\n",
      "b'yoghurt'\n",
      "b'styrofoam'\n",
      "b'matzoh'\n",
      "b'casserole'\n",
      "b'rayon'\n",
      "b'teaspoons'\n",
      "b'clove'\n",
      "b'durum'\n",
      "b'scorch'\n",
      "b'rtd'\n",
      "b'baccal'\n",
      "b'legumes'\n",
      "b'rhubarb'\n",
      "b'fresher'\n",
      "b'absinth'\n",
      "b'schlenkerla'\n",
      "b'pizzas'\n",
      "b'meaty'\n",
      "b'bratwurst'\n",
      "b'bento'\n",
      "b'hamon'\n",
      "b'ciders'\n",
      "b'trifle'\n",
      "b'truffles'\n",
      "b'malty'\n",
      "b'waffle'\n",
      "b'ricotta'\n",
      "b'quince'\n",
      "b'fillings'\n",
      "b'sugary'\n",
      "b'kir'\n",
      "b'servings'\n",
      "b'intoxicating'\n",
      "b'milkshake'\n",
      "b'uncooked'\n",
      "b'artichokes'\n",
      "b'oul'\n",
      "b'gouda'\n",
      "b'diced'\n",
      "b'unappealing'\n",
      "b'loaves'\n",
      "b'garnishes'\n",
      "b'imbedded'\n",
      "b'dairies'\n",
      "b'pillows'\n",
      "b'frosted'\n",
      "b'congeners'\n",
      "b'microbreweries'\n",
      "b'plantains'\n",
      "b'soothing'\n",
      "b'breakfasts'\n",
      "b'chickpea'\n",
      "b'plied'\n",
      "b'taco'\n",
      "b'fain'\n",
      "b'queso'\n",
      "b'bulgogi'\n",
      "b'choy'\n",
      "b'shoestring'\n",
      "b'limon'\n",
      "b'cabbages'\n",
      "b'puree'\n",
      "b'mul'\n",
      "b'gooseberry'\n",
      "b'oolong'\n",
      "b'tuan'\n",
      "b'oatmeal'\n",
      "b'jjigae'\n",
      "b'gastronomique'\n",
      "b'brownies'\n",
      "b'meknes'\n",
      "b'hotdog'\n",
      "b'buttery'\n",
      "b'parmesan'\n",
      "b'pretzel'\n",
      "b'bearnaise'\n",
      "b'sultanas'\n",
      "b'soya'\n",
      "b'paprika'\n",
      "b'pecans'\n",
      "b'redfish'\n",
      "b'prune'\n",
      "b'beancurd'\n",
      "b'masa'\n",
      "b'twinkies'\n",
      "b'silage'\n",
      "b'rauchbier'\n",
      "b'okra'\n",
      "b'boned'\n",
      "b'faeries'\n",
      "b'gorgonzola'\n",
      "b'couverture'\n",
      "b'camembert'\n",
      "b'feta'\n",
      "b'toque'\n",
      "b'sprouting'\n",
      "b'arrowroot'\n",
      "b'emulsified'\n",
      "b'kebab'\n",
      "b'schnapps'\n",
      "b'gratefully'\n",
      "b'whiskies'\n",
      "b'chillis'\n",
      "b'unprocessed'\n",
      "b'shiro'\n",
      "b'fishmeal'\n",
      "b'appetizers'\n",
      "b'maceration'\n",
      "b'organics'\n",
      "b'coagulated'\n",
      "b'flake'\n",
      "b'froth'\n",
      "b'condiment'\n",
      "b'garnished'\n",
      "b'cornmeal'\n",
      "b'tortillas'\n",
      "b'mojitos'\n",
      "b'spicier'\n",
      "b'cabernet'\n",
      "b'candied'\n",
      "b'wasabi'\n",
      "b'horseradish'\n",
      "b'inedible'\n",
      "b'emulsifier'\n",
      "b'raspberries'\n",
      "b'apfelwein'\n",
      "b'berbere'\n",
      "b'azuki'\n",
      "b'ravioli'\n",
      "b'chantilly'\n",
      "b'tacos'\n",
      "b'caramel'\n",
      "b'grated'\n",
      "b'maki'\n",
      "b'smirnoff'\n",
      "b'tamarind'\n",
      "b'tzle'\n",
      "b'consumables'\n",
      "b'seltzer'\n",
      "b'mandioca'\n",
      "b'currants'\n",
      "b'suey'\n",
      "b'porcini'\n",
      "b'cognac'\n",
      "b'leavened'\n",
      "b'doppelbocks'\n",
      "b'entrees'\n",
      "b'nori'\n",
      "b'viscera'\n",
      "b'natto'\n",
      "b'glycerin'\n",
      "b'salami'\n",
      "b'ravioles'\n",
      "b'gastronomical'\n",
      "b'lithia'\n",
      "b'urquell'\n",
      "b'overheated'\n",
      "b'mugs'\n",
      "b'artichoke'\n",
      "b'whine'\n",
      "b'borscht'\n",
      "b'chevon'\n",
      "b'soju'\n",
      "b'pecorino'\n",
      "b'marshmallow'\n",
      "b'shallots'\n",
      "b'angostura'\n",
      "b'rinsed'\n",
      "b'roquefort'\n",
      "b'laxative'\n",
      "b'coir'\n",
      "b'chewy'\n",
      "b'skewers'\n",
      "b'poultice'\n",
      "b'wonton'\n",
      "b'mangoes'\n",
      "b'puffed'\n",
      "b'funghi'\n",
      "b'homebrewing'\n",
      "b'buttered'\n",
      "b'deli'\n",
      "b'rehydration'\n"
     ]
    }
   ],
   "source": [
    "for s in model._id2word[res]:\n",
    "    print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "res = np.where(assignments==203)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'languages'\n",
      "b'ethnic'\n",
      "b'spoken'\n",
      "b'portuguese'\n",
      "b'tribes'\n",
      "b'peoples'\n",
      "b'asian'\n",
      "b'speak'\n",
      "b'inhabitants'\n",
      "b'speakers'\n",
      "b'muslims'\n",
      "b'minority'\n",
      "b'indo'\n",
      "b'indigenous'\n",
      "b'basque'\n",
      "b'tribe'\n",
      "b'indians'\n",
      "b'immigrants'\n",
      "b'europeans'\n",
      "b'slavic'\n",
      "b'nationality'\n",
      "b'proto'\n",
      "b'arabs'\n",
      "b'inhabited'\n",
      "b'albanian'\n",
      "b'literacy'\n",
      "b'inuit'\n",
      "b'tribal'\n",
      "b'adjective'\n",
      "b'ancestors'\n",
      "b'ancestry'\n",
      "b'armenian'\n",
      "b'households'\n",
      "b'russians'\n",
      "b'malay'\n",
      "b'vietnamese'\n",
      "b'minorities'\n",
      "b'blacks'\n",
      "b'diaspora'\n",
      "b'africans'\n",
      "b'berber'\n",
      "b'aryan'\n",
      "b'bantu'\n",
      "b'immigrant'\n",
      "b'hispanic'\n",
      "b'foreigners'\n",
      "b'moroccan'\n",
      "b'nomadic'\n",
      "b'afrikaans'\n",
      "b'caucasus'\n",
      "b'afro'\n",
      "b'turkic'\n",
      "b'saharan'\n",
      "b'ori'\n",
      "b'aboriginal'\n",
      "b'tis'\n",
      "b'latino'\n",
      "b'ethnicity'\n",
      "b'maltese'\n",
      "b'finns'\n",
      "b'creole'\n",
      "b'australians'\n",
      "b'sino'\n",
      "b'dravidian'\n",
      "b'bilingual'\n",
      "b'basques'\n",
      "b'lao'\n",
      "b'bosnian'\n",
      "b'finno'\n",
      "b'ethnically'\n",
      "b'kurds'\n",
      "b'yiddish'\n",
      "b'asiatic'\n",
      "b'ugric'\n",
      "b'zulu'\n",
      "b'ethnologue'\n",
      "b'haitian'\n",
      "b'mongolian'\n",
      "b'caucasian'\n",
      "b'ainu'\n",
      "b'polynesian'\n",
      "b'burmese'\n",
      "b'migrations'\n",
      "b'moldovan'\n",
      "b'eritrean'\n",
      "b'nationalities'\n",
      "b'columbian'\n",
      "b'kazakh'\n",
      "b'assimilated'\n",
      "b'lingua'\n",
      "b'corsican'\n",
      "b'malays'\n",
      "b'migrants'\n",
      "b'koreans'\n",
      "b'liberian'\n",
      "b'galician'\n",
      "b'nigerian'\n",
      "b'armenians'\n",
      "b'assimilation'\n",
      "b'choctaw'\n",
      "b'kinship'\n",
      "b'francophone'\n",
      "b'anglophone'\n",
      "b'aryans'\n",
      "b'swedes'\n",
      "b'somali'\n",
      "b'sizable'\n",
      "b'inhabiting'\n",
      "b'fijian'\n",
      "b'anatolian'\n",
      "b'hungarians'\n",
      "b'eskimo'\n",
      "b'asians'\n",
      "b'sami'\n",
      "b'cypriots'\n",
      "b'cubans'\n",
      "b'amerindian'\n",
      "b'stateless'\n",
      "b'siberian'\n",
      "b'castes'\n",
      "b'ukrainians'\n",
      "b'franca'\n",
      "b'settler'\n",
      "b'romanians'\n",
      "b'predominate'\n",
      "b'latvians'\n",
      "b'laborers'\n",
      "b'maasai'\n",
      "b'swahili'\n",
      "b'migrating'\n",
      "b'emigrants'\n",
      "b'ladino'\n",
      "b'mayan'\n",
      "b'khoisan'\n",
      "b'sardinian'\n",
      "b'pidgin'\n",
      "b'kazakhs'\n",
      "b'congolese'\n",
      "b'nomads'\n",
      "b'berbers'\n",
      "b'finnic'\n",
      "b'iranians'\n",
      "b'descendents'\n",
      "b'cushitic'\n",
      "b'altaic'\n",
      "b'acadian'\n",
      "b'uralic'\n",
      "b'linguistically'\n",
      "b'desi'\n",
      "b'aztecs'\n",
      "b'bambara'\n",
      "b'multicultural'\n",
      "b'intermarriage'\n",
      "b'malagasy'\n",
      "b'boers'\n",
      "b'inuktitut'\n",
      "b'belgians'\n",
      "b'percentages'\n",
      "b'ethiopians'\n",
      "b'fam'\n",
      "b'afar'\n",
      "b'hausa'\n",
      "b'gypsies'\n",
      "b'expatriates'\n",
      "b'valencian'\n",
      "b'navajo'\n",
      "b'gatherer'\n",
      "b'guinean'\n",
      "b'arawak'\n",
      "b'aleut'\n",
      "b'tamils'\n",
      "b'repatriation'\n",
      "b'gatherers'\n",
      "b'javanese'\n",
      "b'akan'\n",
      "b'xinjiang'\n",
      "b'labourers'\n",
      "b'displacing'\n",
      "b'tamazight'\n",
      "b'tatars'\n",
      "b'angolan'\n",
      "b'maronites'\n",
      "b'hutu'\n",
      "b'chechens'\n",
      "b'secessionist'\n",
      "b'guyanese'\n",
      "b'exterminated'\n",
      "b'literatures'\n",
      "b'afrikaners'\n",
      "b'chadic'\n",
      "b'hakka'\n",
      "b'uzbek'\n",
      "b'amerindians'\n",
      "b'mestizo'\n",
      "b'tatar'\n",
      "b'croat'\n",
      "b'mulatto'\n",
      "b'ethnicities'\n",
      "b'predominates'\n",
      "b'mexicans'\n",
      "b'gibraltarians'\n",
      "b'algonquian'\n",
      "b'kongo'\n",
      "b'tuareg'\n",
      "b'hmong'\n",
      "b'brazilians'\n",
      "b'inhabitant'\n",
      "b'carib'\n",
      "b'dari'\n",
      "b'gaeltacht'\n",
      "b'shamanism'\n",
      "b'afrikaner'\n",
      "b'sedentary'\n",
      "b'admixture'\n",
      "b'bedouin'\n",
      "b'timorese'\n",
      "b'dravidians'\n",
      "b'estonians'\n",
      "b'malabar'\n",
      "b'ewe'\n",
      "b'occitan'\n",
      "b'cree'\n",
      "b'commoners'\n",
      "b'greenlandic'\n",
      "b'serbo'\n",
      "b'mozambican'\n",
      "b'moldovans'\n",
      "b'colonize'\n",
      "b'mapuche'\n",
      "b'caribs'\n",
      "b'quechua'\n",
      "b'chamorro'\n",
      "b'austronesian'\n",
      "b'haitians'\n",
      "b'alemannic'\n",
      "b'cameroonian'\n",
      "b'luxembourgish'\n",
      "b'choctaws'\n",
      "b'noirs'\n",
      "b'baloch'\n",
      "b'filipinos'\n",
      "b'balts'\n",
      "b'ojibwe'\n",
      "b'fluency'\n",
      "b'fluently'\n",
      "b'gabonese'\n",
      "b'gagauz'\n",
      "b'azeri'\n",
      "b'belarusians'\n",
      "b'micronesian'\n",
      "b'bosniaks'\n",
      "b'acadians'\n",
      "b'isolates'\n",
      "b'fulani'\n",
      "b'discriminated'\n",
      "b'liberians'\n",
      "b'levantine'\n",
      "b'francophones'\n",
      "b'gaeilge'\n",
      "b'hopi'\n",
      "b'georgians'\n",
      "b'turkmen'\n",
      "b'unclassified'\n",
      "b'animist'\n",
      "b'paleo'\n",
      "b'kwakiutl'\n",
      "b'andamanese'\n",
      "b'distantly'\n",
      "b'scandinavians'\n",
      "b'bushmen'\n",
      "b'hazaras'\n",
      "b'abkhazians'\n",
      "b'ancestries'\n",
      "b'tagalog'\n",
      "b'brahui'\n",
      "b'yoruba'\n",
      "b'laotian'\n",
      "b'mesoamerican'\n",
      "b'xhosa'\n",
      "b'limburgish'\n",
      "b'genealogists'\n",
      "b'endogamous'\n",
      "b'matrilineal'\n",
      "b'populate'\n",
      "b'americo'\n",
      "b'diverging'\n",
      "b'taino'\n",
      "b'multiracial'\n",
      "b'pejoratively'\n",
      "b'expellees'\n",
      "b'incl'\n",
      "b'slovene'\n",
      "b'ethno'\n",
      "b'slovaks'\n",
      "b'bahasa'\n",
      "b'basotho'\n",
      "b'fijians'\n",
      "b'brahmins'\n",
      "b'rif'\n",
      "b'eritreans'\n",
      "b'eskimos'\n",
      "b'oromo'\n",
      "b'resettlement'\n",
      "b'kickapoo'\n",
      "b'yupik'\n",
      "b'uzbeks'\n",
      "b'algerians'\n",
      "b'sotho'\n",
      "b'vocabularies'\n",
      "b'assimilate'\n",
      "b'omotic'\n",
      "b'gallurese'\n",
      "b'typological'\n",
      "b'melanesian'\n",
      "b'kmaq'\n",
      "b'briton'\n",
      "b'nubian'\n",
      "b'patois'\n",
      "b'marshallese'\n",
      "b'intelligibility'\n",
      "b'olmec'\n",
      "b'ricans'\n",
      "b'amazonian'\n",
      "b'sauk'\n",
      "b'aborigines'\n",
      "b'moroccans'\n",
      "b'adamic'\n",
      "b'indonesians'\n",
      "b'balto'\n",
      "b'aleuts'\n",
      "b'mande'\n",
      "b'beja'\n",
      "b'pygmies'\n",
      "b'bilingualism'\n",
      "b'malayo'\n",
      "b'predominated'\n",
      "b'burman'\n",
      "b'homogenous'\n",
      "b'salish'\n",
      "b'noi'\n",
      "b'shamanic'\n",
      "b'blackfoot'\n",
      "b'mam'\n",
      "b'sinhalese'\n",
      "b'mongoloid'\n",
      "b'mestizos'\n",
      "b'chippewa'\n",
      "b'unmixed'\n",
      "b'celtiberian'\n",
      "b'zaghawa'\n",
      "b'mesoamerica'\n",
      "b'chamorros'\n",
      "b'nilo'\n",
      "b'bedouins'\n",
      "b'rriais'\n",
      "b'emancipated'\n",
      "b'chickasaw'\n",
      "b'kabyle'\n",
      "b'kashubians'\n",
      "b'hazara'\n",
      "b'intermarried'\n",
      "b'cham'\n",
      "b'subdivide'\n",
      "b'anglophones'\n",
      "b'apportioned'\n",
      "b'ciboney'\n",
      "b'connemara'\n",
      "b'slovenians'\n",
      "b'romany'\n",
      "b'tigre'\n",
      "b'comers'\n",
      "b'colonizing'\n",
      "b'keralites'\n",
      "b'mizrahi'\n",
      "b'aranese'\n",
      "b'mingled'\n",
      "b'bengalis'\n",
      "b'amharic'\n",
      "b'galatian'\n",
      "b'miao'\n",
      "b'austroasiatic'\n",
      "b'lunda'\n",
      "b'nostratic'\n",
      "b'pakistanis'\n",
      "b'patrilineal'\n",
      "b'toponyms'\n",
      "b'ojibwa'\n",
      "b'mandalay'\n",
      "b'moravians'\n",
      "b'catalans'\n",
      "b'sesotho'\n",
      "b'hispanics'\n",
      "b'areal'\n",
      "b'khoi'\n",
      "b'verdean'\n",
      "b'fishers'\n",
      "b'ibero'\n",
      "b'centum'\n",
      "b'satem'\n",
      "b'refering'\n",
      "b'uprooted'\n",
      "b'papuan'\n",
      "b'landholders'\n",
      "b'pashto'\n",
      "b'klamath'\n",
      "b'guarani'\n",
      "b'masai'\n",
      "b'amhara'\n",
      "b'issas'\n",
      "b'easterners'\n",
      "b'kambojas'\n",
      "b'malaysians'\n",
      "b'baka'\n",
      "b'nguni'\n",
      "b'uranhay'\n",
      "b'hollandic'\n",
      "b'peopled'\n",
      "b'ndebele'\n",
      "b'creoles'\n",
      "b'bushman'\n",
      "b'tibeto'\n",
      "b'herero'\n",
      "b'zapotec'\n",
      "b'substratum'\n",
      "b'splintered'\n",
      "b'circassians'\n",
      "b'animists'\n",
      "b'upc'\n",
      "b'burkinabe'\n",
      "b'hamitic'\n",
      "b'montenegrins'\n",
      "b'jati'\n",
      "b'mossi'\n",
      "b'diasporas'\n",
      "b'jamaicans'\n",
      "b'immigrate'\n",
      "b'joual'\n",
      "b'mandaeans'\n",
      "b'anasazi'\n",
      "b'amazigh'\n",
      "b'aymara'\n",
      "b'kipsigis'\n",
      "b'altay'\n",
      "b'yemenite'\n",
      "b'kordofanian'\n",
      "b'coloureds'\n",
      "b'nilotic'\n",
      "b'mountaineers'\n",
      "b'ehret'\n",
      "b'lusitanian'\n",
      "b'quebecers'\n",
      "b'soninke'\n",
      "b'fon'\n",
      "b'chuvash'\n",
      "b'chaker'\n",
      "b'bamar'\n",
      "b'natufian'\n",
      "b'shona'\n",
      "b'guatemalans'\n",
      "b'miscegenation'\n",
      "b'tigrinya'\n",
      "b'friulian'\n",
      "b'igbo'\n",
      "b'osage'\n",
      "b'chattel'\n",
      "b'cherokees'\n",
      "b'nuba'\n",
      "b'uncivilized'\n",
      "b'somalis'\n",
      "b'compatriots'\n",
      "b'cumbric'\n",
      "b'khoikhoi'\n",
      "b'maroons'\n",
      "b'macanese'\n",
      "b'sacagawea'\n",
      "b'latinos'\n",
      "b'acculturation'\n",
      "b'alaskans'\n",
      "b'lenape'\n",
      "b'uighur'\n",
      "b'maka'\n",
      "b'ethnographers'\n",
      "b'chiefdoms'\n",
      "b'bretons'\n",
      "b'mauritians'\n",
      "b'beti'\n",
      "b'verdeans'\n",
      "b'japonic'\n",
      "b'colombians'\n",
      "b'dua'\n",
      "b'afars'\n",
      "b'bangladeshis'\n",
      "b'kanembu'\n",
      "b'sinti'\n",
      "b'krahn'\n",
      "b'hamito'\n",
      "b'sylheti'\n",
      "b'bubi'\n",
      "b'arabized'\n",
      "b'qinghai'\n",
      "b'fante'\n",
      "b'kushans'\n",
      "b'civilize'\n",
      "b'yup'\n",
      "b'resettle'\n",
      "b'potawatomi'\n",
      "b'mongoloids'\n",
      "b'tswana'\n",
      "b'tupi'\n",
      "b'lingual'\n",
      "b'fula'\n",
      "b'soso'\n",
      "b'tetum'\n",
      "b'bajan'\n",
      "b'bandanese'\n",
      "b'bakongo'\n",
      "b'missourians'\n",
      "b'kriol'\n",
      "b'logudorese'\n",
      "b'wolof'\n",
      "b'caucasoid'\n",
      "b'caucasians'\n",
      "b'hutterite'\n",
      "b'chukchi'\n",
      "b'tocharians'\n",
      "b'euskara'\n",
      "b'borderlands'\n",
      "b'tungusic'\n",
      "b'pisin'\n",
      "b'guaran'\n",
      "b'apaches'\n",
      "b'tamasheq'\n",
      "b'lowlanders'\n",
      "b'nigerians'\n",
      "b'autochthonous'\n",
      "b'iberians'\n",
      "b'vascones'\n",
      "b'cajuns'\n",
      "b'demographically'\n",
      "b'tifinagh'\n",
      "b'dagestani'\n",
      "b'gros'\n",
      "b'herzegovinian'\n",
      "b'garifuna'\n",
      "b'laotians'\n",
      "b'urnfield'\n",
      "b'sylhet'\n",
      "b'azeris'\n",
      "b'maldivians'\n",
      "b'mixtec'\n",
      "b'balochi'\n",
      "b'unrecognised'\n",
      "b'marginalization'\n",
      "b'flemings'\n",
      "b'dioula'\n",
      "b'maur'\n",
      "b'geopolitically'\n",
      "b'tsonga'\n",
      "b'voortrekker'\n",
      "b'kalmyk'\n",
      "b'khalkha'\n",
      "b'hawaiians'\n",
      "b'kachin'\n",
      "b'azerbaijanis'\n",
      "b'antillean'\n",
      "b'multiethnic'\n",
      "b'caymanian'\n",
      "b'pahuin'\n",
      "b'tarifit'\n",
      "b'livonians'\n",
      "b'batswana'\n",
      "b'assimilating'\n",
      "b'abn'\n",
      "b'athabaskan'\n",
      "b'enslave'\n",
      "b'meroitic'\n",
      "b'lgiy'\n",
      "b'nubians'\n",
      "b'gallura'\n",
      "b'iwi'\n",
      "b'herdsmen'\n",
      "b'zuni'\n",
      "b'plas'\n",
      "b'altai'\n",
      "b'tland'\n",
      "b'albertans'\n",
      "b'ugrian'\n",
      "b'keh'\n",
      "b'arabization'\n",
      "b'iranic'\n",
      "b'mandinka'\n",
      "b'haredim'\n",
      "b'urheimat'\n",
      "b'vernaculars'\n",
      "b'tocharian'\n",
      "b'blackfeet'\n",
      "b'interlanguage'\n",
      "b'campesinos'\n",
      "b'gitanos'\n",
      "b'polynesians'\n",
      "b'aquitanian'\n",
      "b'sudanic'\n",
      "b'jomon'\n",
      "b'bassa'\n",
      "b'guangxi'\n",
      "b'tuaregs'\n",
      "b'clines'\n",
      "b'pritsak'\n",
      "b'assiniboine'\n",
      "b'caddo'\n",
      "b'setswana'\n",
      "b'inuvialuit'\n",
      "b'interethnic'\n",
      "b'adamawa'\n",
      "b'colonizers'\n",
      "b'romansh'\n",
      "b'romanisation'\n",
      "b'wyandot'\n",
      "b'ecuadorians'\n",
      "b'sorbs'\n",
      "b'torlakian'\n",
      "b'aeta'\n",
      "b'heritages'\n",
      "b'pieds'\n",
      "b'kiswahili'\n",
      "b'erythraean'\n",
      "b'apace'\n",
      "b'toponymy'\n",
      "b'kipchak'\n",
      "b'cultivators'\n",
      "b'orkhon'\n",
      "b'greenlanders'\n",
      "b'vlachs'\n",
      "b'papiamento'\n",
      "b'plautdietsch'\n",
      "b'quebecois'\n",
      "b'tumbuka'\n",
      "b'masaki'\n",
      "b'inari'\n",
      "b'tlingit'\n",
      "b'seminomadic'\n",
      "b'balochis'\n",
      "b'equatoguinean'\n",
      "b'tuniit'\n",
      "b'rakhine'\n",
      "b'sandawe'\n",
      "b'gibraltarian'\n",
      "b'kirundi'\n",
      "b'daerah'\n",
      "b'barbadian'\n",
      "b'govigama'\n",
      "b'elamo'\n",
      "b'familycolor'\n",
      "b'lingala'\n",
      "b'ryukyuans'\n",
      "b'armorica'\n",
      "b'pirah'\n",
      "b'hovd'\n",
      "b'serres'\n",
      "b'malintzin'\n",
      "b'kimbundu'\n",
      "b'mulattos'\n",
      "b'criollos'\n",
      "b'nicaraguans'\n",
      "b'bicontinental'\n",
      "b'bosnians'\n",
      "b'buryat'\n",
      "b'siais'\n",
      "b'abunda'\n",
      "b'otoe'\n",
      "b'bamileke'\n",
      "b'subjugate'\n",
      "b'tachelhit'\n",
      "b'uyghur'\n",
      "b'buraku'\n",
      "b'viracocha'\n",
      "b'jordanians'\n",
      "b'sundanese'\n",
      "b'lites'\n",
      "b'makah'\n",
      "b'samoans'\n",
      "b'kaw'\n",
      "b'reo'\n",
      "b'batak'\n",
      "b'tibetans'\n",
      "b'borkou'\n",
      "b'snowshoe'\n",
      "b'grenadian'\n",
      "b'illiniwek'\n",
      "b'madurese'\n",
      "b'ethnolinguistic'\n",
      "b'nasrani'\n",
      "b'prehispanic'\n",
      "b'ryukyuan'\n",
      "b'pueblos'\n",
      "b'syriacs'\n",
      "b'enumerate'\n",
      "b'omani'\n",
      "b'latgalian'\n",
      "b'afroasiatic'\n",
      "b'aunus'\n",
      "b'barbadians'\n",
      "b'capitalising'\n",
      "b'theung'\n",
      "b'knanaya'\n",
      "b'tigrigna'\n",
      "b'maliseet'\n",
      "b'abenaki'\n",
      "b'zande'\n",
      "b'kathakali'\n",
      "b'argentinians'\n",
      "b'mandjia'\n",
      "b'yakoma'\n",
      "b'peuhl'\n",
      "b'zenati'\n",
      "b'gaelg'\n",
      "b'comorians'\n",
      "b'unadded'\n",
      "b'washoe'\n",
      "b'mandara'\n",
      "b'longhouse'\n",
      "b'kalaallisut'\n",
      "b'sociologically'\n",
      "b'dakotas'\n",
      "b'disjunct'\n",
      "b'rhaeto'\n",
      "b'amerind'\n",
      "b'ovimbundu'\n",
      "b'colonising'\n",
      "b'linguasphere'\n",
      "b'zenaga'\n",
      "b'moshi'\n",
      "b'baluchi'\n",
      "b'siouan'\n",
      "b'malinke'\n",
      "b'maras'\n",
      "b'sicilians'\n",
      "b'inupiatun'\n",
      "b'makua'\n",
      "b'territorially'\n",
      "b'fenno'\n",
      "b'siboney'\n",
      "b'dene'\n",
      "b'baluch'\n",
      "b'ibadan'\n",
      "b'buganda'\n",
      "b'mandingo'\n",
      "b'tonkawa'\n",
      "b'mesti'\n",
      "b'montagnais'\n",
      "b'decimation'\n",
      "b'peruvians'\n",
      "b'belizeans'\n",
      "b'bajans'\n",
      "b'mozarabic'\n",
      "b'bashkir'\n",
      "b'peloponnesos'\n",
      "b'guamanian'\n",
      "b'outcaste'\n",
      "b'permic'\n",
      "b'lappic'\n",
      "b'trekboers'\n",
      "b'tsimshian'\n",
      "b'germanised'\n",
      "b'negroid'\n",
      "b'kickapoos'\n",
      "b'ndau'\n",
      "b'loum'\n",
      "b'miskito'\n",
      "b'etzion'\n",
      "b'nyanja'\n",
      "b'jats'\n",
      "b'hassaniya'\n",
      "b'guanches'\n",
      "b'floridians'\n",
      "b'institutionally'\n",
      "b'ngoni'\n",
      "b'ibge'\n",
      "b'aborigine'\n",
      "b'dogon'\n",
      "b'scotti'\n",
      "b'semetic'\n",
      "b'sakalava'\n",
      "b'baya'\n",
      "b'raggae'\n",
      "b'njem'\n",
      "b'metics'\n",
      "b'klingonaase'\n",
      "b'mtdna'\n",
      "b'circassian'\n",
      "b'cjk'\n",
      "b'gondi'\n",
      "b'kpelle'\n",
      "b'missouria'\n",
      "b'betawi'\n",
      "b'gaeltachta'\n",
      "b'bugis'\n",
      "b'bila'\n",
      "b'hisabetsu'\n",
      "b'ossetians'\n",
      "b'tikar'\n",
      "b'omeljan'\n",
      "b'kikuyu'\n",
      "b'europeanists'\n",
      "b'idiosyncracies'\n",
      "b'maravi'\n",
      "b'japhetic'\n",
      "b'karelians'\n",
      "b'anglic'\n",
      "b'segregating'\n",
      "b'candombl'\n",
      "b'karaim'\n"
     ]
    }
   ],
   "source": [
    "for s in model._id2word[res]:\n",
    "    print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nemb = tf.nn.l2_normalize(model._w_in, 1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
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