Example solution to Udacity Deep Learning course assignment 5 -- W2V CBOW

5_word2vec.ipynb

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    "Deep Learning\n",
    "=============\n",
    "\n",
    "Assignment 5\n",
    "------------\n",
    "\n",
    "The goal of this assignment is to train a Word2Vec skip-gram model over [Text8](http://mattmahoney.net/dc/textdata) data."
   ]
  },
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    "# These are all the modules we'll be using later. Make sure you can import them\n",
    "# before proceeding further.\n",
    "%matplotlib inline\n",
    "from __future__ import print_function\n",
    "import collections\n",
    "import math\n",
    "import numpy as np\n",
    "import os\n",
    "import random\n",
    "import tensorflow as tf\n",
    "import zipfile\n",
    "from matplotlib import pylab\n",
    "from six.moves import range\n",
    "from six.moves.urllib.request import urlretrieve\n",
    "from sklearn.manifold import TSNE"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "Download the data from the source website if necessary."
   ]
  },
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found and verified text8.zip\n"
     ]
    }
   ],
   "source": [
    "url = 'http://mattmahoney.net/dc/'\n",
    "\n",
    "def maybe_download(filename, expected_bytes):\n",
    "  \"\"\"Download a file if not present, and make sure it's the right size.\"\"\"\n",
    "  if not os.path.exists(filename):\n",
    "    filename, _ = urlretrieve(url + filename, filename)\n",
    "  statinfo = os.stat(filename)\n",
    "  if statinfo.st_size == expected_bytes:\n",
    "    print('Found and verified %s' % filename)\n",
    "  else:\n",
    "    print(statinfo.st_size)\n",
    "    raise Exception(\n",
    "      'Failed to verify ' + filename + '. Can you get to it with a browser?')\n",
    "  return filename\n",
    "\n",
    "filename = maybe_download('text8.zip', 31344016)"
   ]
  },
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   "source": [
    "Read the data into a string."
   ]
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data size 17005207\n"
     ]
    }
   ],
   "source": [
    "def read_data(filename):\n",
    "  \"\"\"Extract the first file enclosed in a zip file as a list of words\"\"\"\n",
    "  with zipfile.ZipFile(filename) as f:\n",
    "    data = tf.compat.as_str(f.read(f.namelist()[0])).split()\n",
    "  return data\n",
    "  \n",
    "words = read_data(filename)\n",
    "print('Data size %d' % len(words))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Zdw6i4F8glpp"
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   "source": [
    "Build the dictionary and replace rare words with UNK token."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# <S>, </S>, <UNK>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most common words (+UNK) [['UNK', 418391], ('the', 1061396), ('of', 593677), ('and', 416629), ('one', 411764)]\n",
      "Sample data [5239, 3084, 12, 6, 195, 2, 3137, 46, 59, 156]\n"
     ]
    }
   ],
   "source": [
    "vocabulary_size = 50000\n",
    "\n",
    "def build_dataset(words):\n",
    "  count = [['UNK', -1]]\n",
    "  count.extend(collections.Counter(words).most_common(vocabulary_size - 1))\n",
    "  dictionary = dict()\n",
    "  for word, _ in count:\n",
    "    dictionary[word] = len(dictionary)\n",
    "  data = list()\n",
    "  unk_count = 0\n",
    "  for word in words:\n",
    "    if word in dictionary:\n",
    "      index = dictionary[word]\n",
    "    else:\n",
    "      index = 0  # dictionary['UNK']\n",
    "      unk_count = unk_count + 1\n",
    "    data.append(index)\n",
    "  count[0][1] = unk_count\n",
    "  reverse_dictionary = dict(zip(dictionary.values(), dictionary.keys())) \n",
    "  return data, count, dictionary, reverse_dictionary\n",
    "\n",
    "data, count, dictionary, reverse_dictionary = build_dataset(words)\n",
    "print('Most common words (+UNK)', count[:5])\n",
    "print('Sample data', data[:10])\n",
    "del words  # Hint to reduce memory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "lFwoyygOmWsL"
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   "source": [
    "Function to generate a training batch for the skip-gram model."
   ]
  },
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   "execution_count": 8,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data: ['anarchism', 'originated', 'as', 'a', 'term', 'of', 'abuse', 'first', 'used', 'against', 'early', 'working', 'class', 'radicals', 'including', 'the']\n",
      "\n",
      "with num_skips = 2 and skip_window = 1:\n",
      "    batch: ['originated', 'originated', 'as', 'as', 'a', 'a', 'term', 'term']\n",
      "    labels: ['anarchism', 'as', 'originated', 'a', 'as', 'term', 'a', 'of']\n",
      "\n",
      "with num_skips = 4 and skip_window = 2:\n",
      "    batch: ['as', 'as', 'as', 'as', 'a', 'a', 'a', 'a']\n",
      "    labels: ['a', 'term', 'originated', 'anarchism', 'term', 'originated', 'as', 'of']\n",
      "\n",
      "with num_skips = 8 and skip_window = 4:\n",
      "    batch: ['term', 'term', 'term', 'term', 'term', 'term', 'term', 'term']\n",
      "    labels: ['of', 'a', 'as', 'abuse', 'originated', 'anarchism', 'first', 'used']\n"
     ]
    }
   ],
   "source": [
    "data_index = 0\n",
    "\n",
    "# skip-gram dataset generation function\n",
    "def generate_batch(batch_size, num_skips, skip_window):\n",
    "  \"\"\"\n",
    "  \n",
    "  Parameters\n",
    "  ----------\n",
    "  num_skips: int : How many times to reuse an input to generate a label.\n",
    "  skips_window: int : How many words to consider left and right.\n",
    "  \n",
    "  \"\"\"\n",
    "  global data_index\n",
    "  assert batch_size % num_skips == 0\n",
    "  assert num_skips <= 2 * skip_window\n",
    "  batch = np.ndarray(shape=(batch_size), dtype=np.int32)\n",
    "  labels = np.ndarray(shape=(batch_size, 1), dtype=np.int32)\n",
    "  span = 2 * skip_window + 1 # [ skip_window target skip_window ]\n",
    "  buffer = collections.deque(maxlen=span)\n",
    "  for _ in range(span):\n",
    "    buffer.append(data[data_index])\n",
    "    data_index = (data_index + 1) % len(data)\n",
    "  for i in range(batch_size // num_skips):\n",
    "    target = skip_window  # target label at the center of the buffer\n",
    "    targets_to_avoid = [ skip_window ]\n",
    "    for j in range(num_skips):\n",
    "      while target in targets_to_avoid:\n",
    "        target = random.randint(0, span - 1)\n",
    "      targets_to_avoid.append(target)\n",
    "      batch[i * num_skips + j] = buffer[skip_window]\n",
    "      labels[i * num_skips + j, 0] = buffer[target]\n",
    "    buffer.append(data[data_index])\n",
    "    data_index = (data_index + 1) % len(data)\n",
    "  return batch, labels\n",
    "\n",
    "print('data:', [reverse_dictionary[di] for di in data[:16]])\n",
    "\n",
    "for num_skips, skip_window in [(2, 1), (4, 2), (8, 4)]:\n",
    "    data_index = 0\n",
    "    batch, labels = generate_batch(batch_size=8, num_skips=num_skips, skip_window=skip_window)\n",
    "    print('\\nwith num_skips = %d and skip_window = %d:' % (num_skips, skip_window))\n",
    "    print('    batch:', [reverse_dictionary[bi] for bi in batch])\n",
    "    print('    labels:', [reverse_dictionary[li] for li in labels.reshape(8)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data: anarchism originated as a term of abuse first used against early working class radicals including the diggers of the english revolution and the sans UNK of the french revolution whilst the term is still used in a pejorative way to describe any act that used violent means to destroy the organization of society it has also been taken up as a positive label by self defined anarchists the word anarchism is derived from the greek without archons ruler chief king anarchism as a political philosophy is the belief that rulers are unnecessary and should be abolished although there are differing\n"
     ]
    }
   ],
   "source": [
    "print('data: {}'.format(' '.join([reverse_dictionary[di] for di in data[:100]])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ofd1MbBuwiva"
   },
   "source": [
    "Train a skip-gram model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
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   "source": [
    "batch_size = 128\n",
    "embedding_size = 128 # Dimension of the embedding vector.\n",
    "skip_window = 1 # How many words to consider left and right.\n",
    "num_skips = 2 # How many times to reuse an input to generate a label.\n",
    "# We pick a random validation set to sample nearest neighbors. here we limit the\n",
    "# validation samples to the words that have a low numeric ID, which by\n",
    "# construction are also the most frequent. \n",
    "valid_size = 16 # Random set of words to evaluate similarity on.\n",
    "valid_window = 100 # Only pick dev samples in the head of the distribution.\n",
    "valid_examples = np.array(random.sample(range(valid_window), valid_size))\n",
    "num_sampled = 64 # Number of negative examples to sample.\n",
    "\n",
    "graph = tf.Graph()\n",
    "\n",
    "with graph.as_default(), tf.device('/cpu:0'):\n",
    "\n",
    "  # Input data.\n",
    "  train_dataset = tf.placeholder(tf.int32, shape=[batch_size])\n",
    "  train_labels = tf.placeholder(tf.int32, shape=[batch_size, 1])\n",
    "  valid_dataset = tf.constant(valid_examples, dtype=tf.int32)\n",
    "  \n",
    "  # Variables.\n",
    "  embeddings = tf.Variable(\n",
    "    tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0))\n",
    "  softmax_weights = tf.Variable(\n",
    "    tf.truncated_normal([vocabulary_size, embedding_size],\n",
    "                         stddev=1.0 / math.sqrt(embedding_size)))\n",
    "  softmax_biases = tf.Variable(tf.zeros([vocabulary_size]))\n",
    "  \n",
    "  # Model.\n",
    "  # Look up embeddings for inputs.\n",
    "  embed = tf.nn.embedding_lookup(embeddings, train_dataset)\n",
    "  # Compute the softmax loss, using a sample of the negative labels each time.\n",
    "  loss = tf.reduce_mean(\n",
    "    tf.nn.sampled_softmax_loss(softmax_weights, softmax_biases, embed,\n",
    "                               train_labels, num_sampled, vocabulary_size))\n",
    "\n",
    "  # Optimizer.\n",
    "  optimizer = tf.train.AdagradOptimizer(1.0).minimize(loss)\n",
    "  \n",
    "  # Compute the similarity between minibatch examples and all embeddings.\n",
    "  # We use the cosine distance:\n",
    "  norm = tf.sqrt(tf.reduce_sum(tf.square(embeddings), 1, keep_dims=True))\n",
    "  normalized_embeddings = embeddings / norm\n",
    "  valid_embeddings = tf.nn.embedding_lookup(\n",
    "    normalized_embeddings, valid_dataset)\n",
    "  similarity = tf.matmul(valid_embeddings, tf.transpose(normalized_embeddings))"
   ]
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    "tf.initialize_all_variables?"
   ]
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     "text": [
      "Initialized\n",
      "Average loss at step 0: 8.280972\n",
      "Nearest to with: bursting, dict, invader, grandsons, pension, paleo, gnat, williams,\n",
      "Nearest to people: yeltsin, triumphantly, electrolytes, emergencies, duvalier, samara, suzaku, tischendorf,\n",
      "Nearest to his: ante, trespass, number, alef, desmond, fainting, inferno, bubi,\n",
      "Nearest to states: alcuin, place, payback, gala, viewers, householder, breach, versailles,\n",
      "Nearest to some: topsoil, rowdy, cmt, childs, kimberly, aztecs, agm, joaqu,\n",
      "Nearest to and: jockeys, nowell, tre, stormed, gliders, flamethrower, admits, worshipped,\n",
      "Nearest to is: balcony, kylix, unipolar, nasa, line, subfamily, willingness, riches,\n",
      "Nearest to s: chanter, mobygames, stylization, fencers, udf, recall, zerby, oath,\n",
      "Nearest to first: princesses, imaginary, neuronal, aphex, ethnological, deum, abnormality, brute,\n",
      "Nearest to this: iberia, fascism, drought, bristol, looksmart, emerson, layer, embroidery,\n",
      "Nearest to use: dcc, monorails, colourless, pacific, jeux, malachi, bakongo, aberrations,\n",
      "Nearest to over: gland, empiricists, implants, proficiency, dealerships, fundamental, munda, suggesting,\n",
      "Nearest to called: karloff, recluse, volcano, kansas, kant, elevates, dmitri, rotates,\n",
      "Nearest to an: nahuatl, contradictions, done, brigadists, vaccinations, detect, bowing, jer,\n",
      "Nearest to the: stuntman, promoter, suffocation, search, ninhursag, modernize, feuerbach, superpowers,\n",
      "Nearest to to: elamites, siddhartha, deranged, bolshevism, less, international, hew, due,\n",
      "Average loss at step 2000: 4.361980\n",
      "Average loss at step 4000: 3.864394\n",
      "Average loss at step 6000: 3.788210\n",
      "Average loss at step 8000: 3.680263\n",
      "Average loss at step 10000: 3.613411\n",
      "Nearest to with: liabilities, in, for, by, strassburg, into, attach, arnaz,\n",
      "Nearest to people: yeltsin, emergencies, triumphantly, extrusive, electrolytes, cassation, eyeball, hourglass,\n",
      "Nearest to his: their, its, s, the, her, encounters, xn, mesopotamian,\n",
      "Nearest to states: payback, viewers, place, alcuin, gala, finno, queensland, mostly,\n",
      "Nearest to some: many, these, seem, remini, other, romita, qc, lingua,\n",
      "Nearest to and: or, but, d, decision, pollute, which, learner, who,\n",
      "Nearest to is: was, are, has, catalyze, unlike, specialized, covalent, were,\n",
      "Nearest to s: his, homonyms, chanter, or, celtics, encounters, teborg, sayers,\n",
      "Nearest to first: sarcastic, thailand, ef, javier, ester, apollo, adjustments, tongs,\n",
      "Nearest to this: it, the, which, jaws, homology, malts, a, inflatable,\n",
      "Nearest to use: dcc, celebrities, pacific, opel, ig, malachi, microsite, jeux,\n",
      "Nearest to over: tuareg, cars, munda, fundamental, dealerships, implants, immorality, gland,\n",
      "Nearest to called: spain, recluse, household, hoist, kansas, volcano, writable, ipsec,\n",
      "Nearest to an: brigadists, detect, elitism, contradictions, done, claudius, nahuatl, the,\n",
      "Nearest to the: this, a, its, his, vocalist, bhopal, rabbinic, their,\n",
      "Nearest to to: freebsd, otto, must, inexplicably, not, cmyk, cambodia, lba,\n",
      "Average loss at step 12000: 3.603784\n",
      "Average loss at step 14000: 3.566328\n",
      "Average loss at step 16000: 3.410636\n",
      "Average loss at step 18000: 3.457990\n",
      "Average loss at step 20000: 3.539080\n",
      "Nearest to with: in, between, for, liabilities, by, at, attach, smirnov,\n",
      "Nearest to people: yeltsin, emergencies, cassation, extrusive, hourglass, electrolytes, hegelians, angels,\n",
      "Nearest to his: their, her, its, the, my, many, equivalency, this,\n",
      "Nearest to states: payback, viewers, scholars, adhemar, queensland, place, idealists, mostly,\n",
      "Nearest to some: many, these, any, several, other, their, seem, both,\n",
      "Nearest to and: or, which, but, since, the, expire, jayne, ploy,\n",
      "Nearest to is: was, has, are, if, cocker, were, be, outnumber,\n",
      "Nearest to s: bicentennial, teborg, humankind, blooded, depraved, item, genitals, the,\n",
      "Nearest to first: second, last, kenny, during, ester, vipassana, javier, thailand,\n",
      "Nearest to this: it, which, a, the, that, what, fascism, not,\n",
      "Nearest to use: celebrities, opel, pacific, ig, microsite, improve, acclamation, dcc,\n",
      "Nearest to over: tuareg, implants, neutralized, fundamental, therese, xt, henson, bruun,\n",
      "Nearest to called: sprague, kansas, writable, spain, household, ariane, addict, df,\n",
      "Nearest to an: claudius, elitism, the, brigadists, ambushes, weekdays, costly, implicated,\n",
      "Nearest to the: its, their, bhopal, his, any, this, a, rabbinic,\n",
      "Nearest to to: not, may, can, would, could, will, must, reassure,\n",
      "Average loss at step 22000: 3.503928\n",
      "Average loss at step 24000: 3.485008\n",
      "Average loss at step 26000: 3.480484\n",
      "Average loss at step 28000: 3.478989\n",
      "Average loss at step 30000: 3.502262\n",
      "Nearest to with: between, attach, using, topologies, southside, in, poodle, into,\n",
      "Nearest to people: angels, hegelians, emergencies, yeltsin, cassation, cases, those, hourglass,\n",
      "Nearest to his: her, their, its, the, my, s, mesopotamian, taped,\n",
      "Nearest to states: payback, viewers, finno, adhemar, detention, panned, mostly, topless,\n",
      "Nearest to some: many, these, several, all, other, both, any, their,\n",
      "Nearest to and: or, but, who, like, learner, in, of, unconventional,\n",
      "Nearest to is: was, has, are, were, cocker, be, does, if,\n",
      "Nearest to s: his, patriarchy, deprivation, unnamed, hertogenbosch, cti, biology, bicentennial,\n",
      "Nearest to first: second, last, thailand, same, present, earliest, ef, next,\n",
      "Nearest to this: it, which, what, fascism, that, his, inflatable, refurbishment,\n",
      "Nearest to use: celebrities, ig, opel, hatred, probing, improve, acclamation, pacific,\n",
      "Nearest to over: implants, therese, xt, bruun, henson, tuareg, fundamental, acuity,\n",
      "Nearest to called: sprague, kansas, writable, oppressed, opus, addict, df, household,\n",
      "Nearest to an: detect, brigadists, claudius, ambushes, elitism, jarrett, nahuatl, aluminium,\n",
      "Nearest to the: its, his, their, spades, sweating, weekdays, some, bhopal,\n",
      "Nearest to to: would, can, reassure, will, could, should, may, indistinguishable,\n",
      "Average loss at step 32000: 3.497887\n",
      "Average loss at step 34000: 3.492487\n",
      "Average loss at step 36000: 3.453658\n",
      "Average loss at step 38000: 3.303102\n",
      "Average loss at step 40000: 3.429431\n",
      "Nearest to with: between, topologies, without, arnaz, mm, liabilities, in, pakistani,\n",
      "Nearest to people: hegelians, angels, capillaries, those, men, scientists, cases, emergencies,\n",
      "Nearest to his: their, her, its, my, the, romita, s, shameless,\n",
      "Nearest to states: kingdom, nations, payback, adhemar, postulated, balkan, ensure, mostly,\n",
      "Nearest to some: many, several, these, any, both, those, qc, most,\n",
      "Nearest to and: or, but, in, however, comedienne, including, bae, k,\n",
      "Nearest to is: was, are, be, has, textbooks, inadvertently, cocker, if,\n",
      "Nearest to s: his, waldensians, humankind, shaun, counterfactual, bicentennial, ethereal, retrospectively,\n",
      "Nearest to first: second, last, next, generalship, during, masses, ani, slays,\n",
      "Nearest to this: which, it, that, the, what, refurbishment, unknown, any,\n",
      "Nearest to use: ig, celebrities, hatred, opel, activate, picchi, probing, acclamation,\n",
      "Nearest to over: xt, tires, drops, bruun, boltzmann, reason, acuity, henson,\n",
      "Nearest to called: used, considered, sprague, residues, opus, skiego, household, deputy,\n",
      "Nearest to an: claudius, ambushes, trucks, brigadists, detect, lorenzo, lambasted, isothermal,\n",
      "Nearest to the: its, his, this, their, spades, a, tricolour, any,\n",
      "Nearest to to: will, reassure, can, could, auctioned, would, may, must,\n",
      "Average loss at step 42000: 3.436611\n",
      "Average loss at step 44000: 3.449719\n",
      "Average loss at step 46000: 3.443792\n",
      "Average loss at step 48000: 3.356486\n",
      "Average loss at step 50000: 3.383287\n",
      "Nearest to with: between, preaching, topologies, by, surprising, kosar, poodle, liabilities,\n",
      "Nearest to people: men, hegelians, angels, cases, emergencies, scientists, years, books,\n",
      "Nearest to his: her, their, its, my, the, your, shameless, him,\n",
      "Nearest to states: kingdom, catalysis, nations, state, balkan, rightmost, ensure, postulated,\n",
      "Nearest to some: many, several, these, both, any, various, those, qc,\n",
      "Nearest to and: or, but, learner, including, of, than, while, replicated,\n",
      "Nearest to is: was, has, are, were, does, became, be, elo,\n",
      "Nearest to s: nucleotide, his, their, patriarchy, juvenal, and, humankind, abugida,\n",
      "Nearest to first: second, last, next, same, celebrity, slays, best, molestation,\n",
      "Nearest to this: which, it, the, cantons, he, refurbishment, inflatable, another,\n",
      "Nearest to use: activate, celebrities, hatred, nitric, formation, ig, regnal, kuomintang,\n",
      "Nearest to over: xt, drops, tires, acuity, along, henson, bruun, tuareg,\n",
      "Nearest to called: used, residues, writable, named, known, benelux, termini, opus,\n",
      "Nearest to an: brigadists, claudius, ambushes, detect, weekdays, aluminium, elitism, infusion,\n",
      "Nearest to the: their, its, this, his, some, cois, spades, bhopal,\n",
      "Nearest to to: reassure, may, should, nls, will, would, can, could,\n",
      "Average loss at step 52000: 3.437631\n",
      "Average loss at step 54000: 3.427063\n",
      "Average loss at step 56000: 3.438622\n",
      "Average loss at step 58000: 3.392574\n",
      "Average loss at step 60000: 3.392098\n",
      "Nearest to with: between, in, liabilities, including, by, penning, misunderstood, topologies,\n",
      "Nearest to people: men, women, countries, scientists, those, others, jews, emergencies,\n",
      "Nearest to his: her, their, my, its, mesopotamian, your, instants, romita,\n",
      "Nearest to states: kingdom, nations, postulated, countries, balkan, state, ensure, seer,\n",
      "Nearest to some: many, several, these, any, both, most, all, those,\n",
      "Nearest to and: or, but, than, hogg, iban, findable, learner, alioth,\n",
      "Nearest to is: was, are, has, although, be, remains, hates, cocker,\n",
      "Nearest to s: firsthand, mathcal, patriarchy, iers, tzi, his, heenan, storehouse,\n",
      "Nearest to first: last, second, next, same, best, earliest, third, molestation,\n",
      "Nearest to this: it, which, that, the, refurbishment, cantons, there, some,\n",
      "Nearest to use: activate, celebrities, hal, headshot, formation, love, deepwater, blade,\n",
      "Nearest to over: around, bruun, along, xt, about, into, boltzmann, through,\n",
      "Nearest to called: used, considered, named, pools, residues, kes, df, referred,\n",
      "Nearest to an: brigadists, claudius, infusion, ambushes, detect, lorenzo, elitism, radha,\n",
      "Nearest to the: their, its, spades, a, this, bhopal, pip, docking,\n",
      "Nearest to to: would, will, may, for, reassure, triple, not, sutras,\n",
      "Average loss at step 62000: 3.239252\n",
      "Average loss at step 64000: 3.259107\n",
      "Average loss at step 66000: 3.399528\n",
      "Average loss at step 68000: 3.394026\n",
      "Average loss at step 70000: 3.359243\n",
      "Nearest to with: between, by, lunisolar, poodle, attach, liabilities, topologies, diamagnetism,\n",
      "Nearest to people: men, women, examples, scientists, cases, americans, emergencies, others,\n",
      "Nearest to his: her, their, my, its, our, your, the, shameless,\n",
      "Nearest to states: kingdom, nations, state, countries, rightmost, rodan, queensland, balkan,\n",
      "Nearest to some: many, several, any, all, these, both, various, the,\n",
      "Nearest to and: or, hosokawa, like, which, but, iban, while, of,\n",
      "Nearest to is: was, has, are, be, cocker, although, remains, in,\n",
      "Nearest to s: firsthand, whose, sayers, humankind, subgenus, chanter, dilution, shaun,\n",
      "Nearest to first: second, last, next, third, earliest, same, molestation, best,\n",
      "Nearest to this: which, it, the, cantons, that, what, some, refurbishment,\n",
      "Nearest to use: headshot, regnal, activate, blade, livers, celebrities, deepwater, formation,\n",
      "Nearest to over: around, xt, about, along, through, across, fundamental, drops,\n",
      "Nearest to called: named, used, considered, residues, df, known, farley, referred,\n",
      "Nearest to an: brigadists, weekdays, detect, claudius, ambushes, davenport, infusion, lorenzo,\n",
      "Nearest to the: their, any, its, this, some, each, a, spades,\n",
      "Nearest to to: can, will, would, must, reassure, may, inexplicably, protruding,\n",
      "Average loss at step 72000: 3.372563\n",
      "Average loss at step 74000: 3.345690\n",
      "Average loss at step 76000: 3.309383\n",
      "Average loss at step 78000: 3.352630\n",
      "Average loss at step 80000: 3.380970\n",
      "Nearest to with: between, into, topologies, legislated, liabilities, aorta, preaching, explanatory,\n",
      "Nearest to people: men, women, years, cases, emergencies, jews, those, scientists,\n",
      "Nearest to his: her, their, my, its, your, our, romita, span,\n",
      "Nearest to states: kingdom, nations, state, countries, rodan, rightmost, balkan, us,\n",
      "Nearest to some: many, several, both, most, various, certain, these, those,\n",
      "Nearest to and: or, but, than, including, like, while, necker, learner,\n",
      "Nearest to is: was, has, are, remains, inadvertently, be, elo, refers,\n",
      "Nearest to s: multinational, orgasm, isbn, cti, nucleotide, abrasion, footage, coaches,\n",
      "Nearest to first: second, last, next, third, same, best, earliest, molestation,\n",
      "Nearest to this: it, which, itself, the, unknown, that, exemplified, belle,\n",
      "Nearest to use: regnal, headshot, blade, livers, brassiere, formation, content, form,\n",
      "Nearest to over: around, across, about, xt, off, along, within, through,\n",
      "Nearest to called: used, named, considered, referred, known, kriegsmarine, granted, twists,\n",
      "Nearest to an: weekdays, claudius, brigadists, trucks, ambushes, radha, lorenzo, infusion,\n",
      "Nearest to the: spades, their, this, a, its, mircea, his, bhopal,\n",
      "Nearest to to: would, reassure, must, should, could, expressly, will, siddhartha,\n",
      "Average loss at step 82000: 3.407849\n",
      "Average loss at step 84000: 3.407846\n",
      "Average loss at step 86000: 3.390482\n",
      "Average loss at step 88000: 3.354193\n",
      "Average loss at step 90000: 3.359430\n",
      "Nearest to with: between, topologies, by, in, liabilities, and, using, without,\n",
      "Nearest to people: men, women, children, emergencies, fans, jews, cases, americans,\n",
      "Nearest to his: her, their, my, its, your, our, the, taped,\n",
      "Nearest to states: kingdom, nations, state, us, countries, rodan, bentine, rightmost,\n",
      "Nearest to some: many, several, these, all, both, certain, any, those,\n",
      "Nearest to and: or, but, including, while, ebne, with, congenital, bands,\n",
      "Nearest to is: was, has, are, does, although, cocker, be, contains,\n",
      "Nearest to s: isbn, firsthand, storehouse, determinants, his, preoccupation, bugle, patriarchy,\n",
      "Nearest to first: second, last, next, earliest, third, best, ani, current,\n",
      "Nearest to this: which, it, the, itself, another, cantons, some, looksmart,\n",
      "Nearest to use: acceptance, regnal, headshot, brassiere, support, content, deepwater, users,\n",
      "Nearest to over: around, across, along, within, xt, complexities, off, about,\n",
      "Nearest to called: named, used, considered, referred, known, designed, notational, granted,\n",
      "Nearest to an: brigadists, weekdays, lorenzo, download, ambushes, emigre, trucks, infusion,\n",
      "Nearest to the: its, spades, this, their, his, each, tricolour, any,\n",
      "Nearest to to: reassure, would, will, nls, towards, shall, supermarket, glendale,\n",
      "Average loss at step 92000: 3.398956\n",
      "Average loss at step 94000: 3.248612\n",
      "Average loss at step 96000: 3.356362\n",
      "Average loss at step 98000: 3.244025\n",
      "Average loss at step 100000: 3.354839\n",
      "Nearest to with: between, in, into, including, telekinetic, hartmann, konkan, mink,\n",
      "Nearest to people: women, men, children, jews, players, fans, cases, countries,\n",
      "Nearest to his: her, their, my, its, your, our, the, s,\n",
      "Nearest to states: nations, kingdom, state, us, countries, seer, rodan, deists,\n",
      "Nearest to some: many, several, these, any, certain, all, both, various,\n",
      "Nearest to and: or, but, like, of, while, however, including, to,\n",
      "Nearest to is: was, has, be, are, refers, became, cocker, remains,\n",
      "Nearest to s: his, firsthand, my, isbn, whose, asclepius, her, sayers,\n",
      "Nearest to first: second, last, next, third, best, same, earliest, original,\n",
      "Nearest to this: which, it, itself, another, the, cantons, weiner, that,\n",
      "Nearest to use: regnal, acceptance, brassiere, headshot, users, support, kuomintang, breakup,\n",
      "Nearest to over: around, across, within, along, xt, salesman, off, about,\n",
      "Nearest to called: named, referred, used, considered, known, designed, marrow, covering,\n",
      "Nearest to an: weekdays, brigadists, claudius, another, infusion, radha, bowing, davenport,\n",
      "Nearest to the: your, their, his, its, this, a, her, some,\n",
      "Nearest to to: will, reassure, would, could, can, and, must, inexplicably,\n"
     ]
    }
   ],
   "source": [
    "num_steps = 100001\n",
    "\n",
    "with tf.Session(graph=graph) as session:\n",
    "  tf.initialize_all_variables().run()\n",
    "  print('Initialized')\n",
    "  average_loss = 0\n",
    "  for step in range(num_steps):\n",
    "    batch_data, batch_labels = generate_batch(\n",
    "      batch_size, num_skips, skip_window)\n",
    "    feed_dict = {train_dataset : batch_data, train_labels : batch_labels}\n",
    "    _, l = session.run([optimizer, loss], feed_dict=feed_dict)\n",
    "#     theano.function([inputs], [outputs])\n",
    "    average_loss += l\n",
    "    if step % 2000 == 0:\n",
    "      if step > 0:\n",
    "        average_loss = average_loss / 2000\n",
    "      # The average loss is an estimate of the loss over the last 2000 batches.\n",
    "      print('Average loss at step %d: %f' % (step, average_loss))\n",
    "      average_loss = 0\n",
    "    # note that this is expensive (~20% slowdown if computed every 500 steps)\n",
    "    if step % 10000 == 0:\n",
    "      sim = similarity.eval()\n",
    "      for i in range(valid_size):\n",
    "        valid_word = reverse_dictionary[valid_examples[i]]\n",
    "        top_k = 8 # number of nearest neighbors\n",
    "        nearest = (-sim[i, :]).argsort()[1:top_k+1]\n",
    "        log = 'Nearest to %s:' % valid_word\n",
    "        for k in range(top_k):\n",
    "          close_word = reverse_dictionary[nearest[k]]\n",
    "          log = '%s %s,' % (log, close_word)\n",
    "        print(log)\n",
    "  final_embeddings = normalized_embeddings.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "cellView": "both",
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "jjJXYA_XzV79"
   },
   "outputs": [],
   "source": [
    "num_points = 400\n",
    "\n",
    "tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=5000)\n",
    "two_d_embeddings = tsne.fit_transform(final_embeddings[1:num_points+1, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "cellView": "both",
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "output_extras": [
      {
       "item_id": 1
      }
     ]
    },
    "colab_type": "code",
    "collapsed": false,
    "executionInfo": {
     "elapsed": 4763,
     "status": "ok",
     "timestamp": 1445965465525,
     "user": {
      "color": "#1FA15D",
      "displayName": "Vincent Vanhoucke",
      "isAnonymous": false,
      "isMe": true,
      "permissionId": "05076109866853157986",
      "photoUrl": "//lh6.googleusercontent.com/-cCJa7dTDcgQ/AAAAAAAAAAI/AAAAAAAACgw/r2EZ_8oYer4/s50-c-k-no/photo.jpg",
      "sessionId": "2f1ffade4c9f20de",
      "userId": "102167687554210253930"
     },
     "user_tz": 420
    },
    "id": "o_e0D_UezcDe",
    "outputId": "df22e4a5-e8ec-4e5e-d384-c6cf37c68c34"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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efvllbDYbXbt2JSIigu7du7Njxw4AUlNTWbRokeNY3t7eAGRmZtKpUyf69OlDUFAQI0eO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\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9Q1w6pbS0tM5yA21FZy3fw2h/wAqCMxiM9sDIyAgXL17EmjVrcPXqVaSnp2Po0KHQ0dEB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\n5AAAAAYj5AAAAAYj5AAAAAbzH+4uu9lEIWMKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2ea662c050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot(embeddings, labels):\n",
    "  assert embeddings.shape[0] >= len(labels), 'More labels than embeddings'\n",
    "  pylab.figure(figsize=(15,15))  # in inches\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',\n",
    "                   ha='right', va='bottom')\n",
    "  pylab.show()\n",
    "\n",
    "words = [reverse_dictionary[i] for i in range(1, num_points+1)]\n",
    "plot(two_d_embeddings, words)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QB5EFrBnpNnc"
   },
   "source": [
    "---\n",
    "\n",
    "Problem\n",
    "-------\n",
    "\n",
    "An alternative to skip-gram is another Word2Vec model called [CBOW](http://arxiv.org/abs/1301.3781) (Continuous Bag of Words). In the CBOW model, instead of predicting a context word from a word vector, you predict a word from the sum of all the word vectors in its context. Implement and evaluate a CBOW model trained on the text8 dataset.\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_index = 0\n",
    "\n",
    "# skip-gram dataset generation function\n",
    "def generate_cbow_batch(batch_size, skip_window):\n",
    "  \"\"\"\n",
    "  \n",
    "  Parameters\n",
    "  ----------\n",
    "  skips_window: int : How many words to consider left and right.\n",
    "  \n",
    "  \"\"\"\n",
    "  global data_index\n",
    "#   assert batch_size % num_skips == 0\n",
    "#   assert num_skips <= 2 * skip_window\n",
    "  batch = np.ndarray(shape=(batch_size, skip_window*2), dtype=np.int32)\n",
    "  labels = np.ndarray(shape=(batch_size,1), dtype=np.int32)\n",
    "\n",
    "  span = 2 * skip_window + 1 # [ skip_window target skip_window ]\n",
    "  buffer = collections.deque(maxlen=span)\n",
    "#   buffer = []\n",
    "  for _ in range(span):\n",
    "    buffer.append(data[data_index])\n",
    "    data_index = (data_index + 1) % len(data)\n",
    "  \n",
    "  for i in range(batch_size):\n",
    "    batch[i] = list(buffer)[:skip_window] + list(buffer)[skip_window+1:]\n",
    "    labels[i] = buffer[skip_window]\n",
    "    buffer.append(data[data_index])\n",
    "    data_index = (data_index + 1) % len(data)\n",
    "    \n",
    "  return batch, labels\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# CBOW model\n",
    "\n",
    "batch_size = 128\n",
    "embedding_size = 128 # Dimension of the embedding vector.\n",
    "skip_window = 1 # How many words to consider left and right.\n",
    "# We pick a random validation set to sample nearest neighbors. here we limit the\n",
    "# validation samples to the words that have a low numeric ID, which by\n",
    "# construction are also the most frequent. \n",
    "valid_size = 16 # Random set of words to evaluate similarity on.\n",
    "valid_window = 100 # Only pick dev samples in the head of the distribution.\n",
    "valid_examples = np.array(random.sample(range(valid_window), valid_size))\n",
    "num_sampled = 64 # Number of negative examples to sample.\n",
    "\n",
    "graph = tf.Graph()\n",
    "\n",
    "with graph.as_default(), tf.device('/cpu:0'):\n",
    "\n",
    "  # Input data.\n",
    "  # note the different input dimensions for the CBOW model\n",
    "  train_dataset = tf.placeholder(tf.int32, shape=[batch_size,skip_window*2])\n",
    "  train_labels = tf.placeholder(tf.int32, shape=[batch_size, 1])\n",
    "  valid_dataset = tf.constant(valid_examples, dtype=tf.int32)\n",
    "  \n",
    "  # Variables.\n",
    "  embeddings = tf.Variable(\n",
    "    tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0))\n",
    "  softmax_weights = tf.Variable(\n",
    "    tf.truncated_normal([vocabulary_size, embedding_size],\n",
    "                         stddev=1.0 / math.sqrt(embedding_size)))\n",
    "  softmax_biases = tf.Variable(tf.zeros([vocabulary_size]))\n",
    "  \n",
    "  # Model.\n",
    "  # Look up embeddings for inputs.\n",
    "  # note the sum over the context embeddings for the CBOW model\n",
    "  embed = tf.nn.embedding_lookup(embeddings, train_dataset)\n",
    "  embed = tf.reduce_sum(embed, 1)\n",
    "\n",
    "  # Compute the softmax loss, using a sample of the negative labels each time.\n",
    "  loss = tf.reduce_mean(\n",
    "    tf.nn.sampled_softmax_loss(softmax_weights, softmax_biases, embed,\n",
    "                               train_labels, num_sampled, vocabulary_size))\n",
    "\n",
    "  # Optimizer.\n",
    "  optimizer = tf.train.AdagradOptimizer(1.0).minimize(loss)\n",
    "\n",
    "  # Compute the similarity between minibatch examples and all embeddings.\n",
    "  # We use the cosine distance:\n",
    "  norm = tf.sqrt(tf.reduce_sum(tf.square(embeddings), 1, keep_dims=True))\n",
    "  normalized_embeddings = embeddings / norm\n",
    "  valid_embeddings = tf.nn.embedding_lookup(\n",
    "    normalized_embeddings, valid_dataset)\n",
    "  similarity = tf.matmul(valid_embeddings, tf.transpose(normalized_embeddings))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialized\n",
      "Average loss at step 0: 7.769947\n",
      "Nearest to for: solutions, guess, cassius, private, balalaika, columbus, monotonicity, beck,\n",
      "Nearest to its: crowns, imre, ax, cockpit, consultative, bluegrass, office, quotient,\n",
      "Nearest to about: harbour, haider, steady, entertaining, instruction, dillinger, bellini, pis,\n",
      "Nearest to four: luster, mycological, etsi, toole, muzzle, posing, niigata, entanglements,\n",
      "Nearest to people: scholes, underwear, eoin, aerobatics, enlightened, caen, jun, saarc,\n",
      "Nearest to all: abdel, arc, laika, seaman, elamite, looking, adventurer, chernobyl,\n",
      "Nearest to system: pressurized, drain, profit, knotted, isomer, madrigals, cmb, gangster,\n",
      "Nearest to i: ligase, lesson, chosen, galician, vernon, hazards, friulian, abraham,\n",
      "Nearest to many: personally, specializations, feelgood, bowden, tiff, manifesting, letterboxing, wallachia,\n",
      "Nearest to had: admin, firefighters, ajmer, gringo, xinhua, fern, elite, dutch,\n",
      "Nearest to war: pythagoras, symphonies, mellaart, labeled, hepatitis, scraped, village, overly,\n",
      "Nearest to nine: blueprint, alpaca, twentieth, frida, khad, bequeathed, saarland, aegis,\n",
      "Nearest to known: maya, cruzi, gees, the, greens, interment, sings, milan,\n",
      "Nearest to six: broke, kirtland, alus, tunnel, kierkegaard, diagnosing, guests, elliptic,\n",
      "Nearest to there: ganesh, wicklow, incentives, feudal, privy, capitol, negatively, breakbeat,\n",
      "Nearest to when: dib, piloted, highbury, superintendence, malaya, recipes, poignant, kri,\n",
      "Average loss at step 2000: 4.098039\n",
      "Average loss at step 4000: 3.563564\n",
      "Average loss at step 6000: 3.391606\n",
      "Average loss at step 8000: 3.239188\n",
      "Average loss at step 10000: 3.178926\n",
      "Nearest to for: with, in, equations, peg, cleavage, bluff, by, rescuing,\n",
      "Nearest to its: their, his, the, enslaved, washes, diffusion, benin, dde,\n",
      "Nearest to about: lugs, marconi, typically, harbour, pentium, zambian, suicides, shorts,\n",
      "Nearest to four: eight, five, six, three, nine, seven, zero, two,\n",
      "Nearest to people: bioleaching, gemini, mckean, lovecraft, comforts, adrian, infrequently, engendered,\n",
      "Nearest to all: these, antinous, croesus, sardinian, abdel, chernobyl, augustinians, many,\n",
      "Nearest to system: finders, unisys, drain, goddess, suicide, chiba, systems, phosphorylation,\n",
      "Nearest to i: periphery, cellular, ii, boson, abraham, sage, coleco, interfered,\n",
      "Nearest to many: some, these, several, other, wallachia, gram, resettle, most,\n",
      "Nearest to had: has, have, was, were, harmonizing, having, rao, finer,\n",
      "Nearest to war: village, penfield, symphonies, jacopo, asphalt, labeled, meditate, durst,\n",
      "Nearest to nine: eight, seven, six, four, five, three, zero, two,\n",
      "Nearest to known: described, lexicographic, used, regarded, seen, gees, discrepancy, expansive,\n",
      "Nearest to six: eight, nine, seven, five, four, three, zero, two,\n",
      "Nearest to there: they, it, he, breakbeat, vitruvius, theobald, inappropriately, incentives,\n",
      "Nearest to when: where, since, superintendence, holy, rudolf, lobe, after, mesh,\n",
      "Average loss at step 12000: 3.198322\n",
      "Average loss at step 14000: 3.152659\n",
      "Average loss at step 16000: 3.181114\n",
      "Average loss at step 18000: 3.120911\n",
      "Average loss at step 20000: 2.991243\n",
      "Nearest to for: pyrimidine, cleavage, creole, after, couplets, expectancies, zealot, dominions,\n",
      "Nearest to its: their, his, the, her, washes, ursa, spartacus, our,\n",
      "Nearest to about: mackay, mourned, africana, mau, lugs, dreamland, volante, muscle,\n",
      "Nearest to four: six, eight, seven, five, three, nine, two, zero,\n",
      "Nearest to people: others, writers, gemini, mboxx, lovecraft, basque, bioleaching, princes,\n",
      "Nearest to all: tolerance, these, sardinian, cyborgs, croesus, peres, both, reichenbach,\n",
      "Nearest to system: systems, unisys, machinations, drain, pilgrimage, finders, solano, intercontinental,\n",
      "Nearest to i: we, ii, he, you, they, budapest, periphery, cellular,\n",
      "Nearest to many: some, several, these, various, most, junkie, resettle, fetishes,\n",
      "Nearest to had: has, have, was, were, having, harmonizing, wankel, rao,\n",
      "Nearest to war: symphonies, village, mongols, penfield, fortieth, labeled, philip, jacopo,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, one,\n",
      "Nearest to known: used, described, such, regarded, seen, interned, lexicographic, served,\n",
      "Nearest to six: five, seven, eight, four, nine, three, zero, two,\n",
      "Nearest to there: they, it, which, he, usually, often, vitruvius, moore,\n",
      "Nearest to when: if, before, where, after, since, during, however, re,\n",
      "Average loss at step 22000: 3.073162\n",
      "Average loss at step 24000: 3.043562\n",
      "Average loss at step 26000: 2.999411\n",
      "Average loss at step 28000: 3.027639\n",
      "Average loss at step 30000: 3.006057\n",
      "Nearest to for: hardens, peg, census, cleavage, without, after, creole, indoors,\n",
      "Nearest to its: their, his, her, washes, the, our, photonic, my,\n",
      "Nearest to about: mourned, mau, mackay, dmu, freshness, morrie, africana, verdean,\n",
      "Nearest to four: six, five, seven, eight, three, nine, two, zero,\n",
      "Nearest to people: others, children, men, gemini, americans, bioleaching, unlike, mboxx,\n",
      "Nearest to all: those, both, each, these, any, playful, some, every,\n",
      "Nearest to system: systems, program, unisys, machinations, unit, ban, lonsdaleite, vga,\n",
      "Nearest to i: we, you, ii, g, budapest, worsened, chukchi, iii,\n",
      "Nearest to many: some, several, these, various, most, other, viz, such,\n",
      "Nearest to had: has, have, was, having, were, knew, received, indirect,\n",
      "Nearest to war: symphonies, temmu, chapter, mongols, fortieth, denham, saboteurs, village,\n",
      "Nearest to nine: eight, seven, six, four, five, three, zero, two,\n",
      "Nearest to known: used, described, regarded, such, defined, seen, interned, decoction,\n",
      "Nearest to six: five, four, seven, eight, nine, three, two, zero,\n",
      "Nearest to there: they, it, he, often, usually, she, these, kr,\n",
      "Nearest to when: if, before, after, while, although, where, during, since,\n",
      "Average loss at step 32000: 2.827495\n",
      "Average loss at step 34000: 2.953936\n",
      "Average loss at step 36000: 2.950162\n",
      "Average loss at step 38000: 2.940475\n",
      "Average loss at step 40000: 2.935153\n",
      "Nearest to for: hardens, while, against, without, after, including, creole, ellipsis,\n",
      "Nearest to its: their, his, her, the, our, my, washes, your,\n",
      "Nearest to about: mourned, mau, machinima, subtitling, nine, africana, mackay, making,\n",
      "Nearest to four: five, six, seven, eight, three, nine, zero, two,\n",
      "Nearest to people: children, men, others, women, authors, americans, those, man,\n",
      "Nearest to all: both, many, any, each, every, some, notions, various,\n",
      "Nearest to system: systems, program, unisys, ban, pilgrimage, nucleons, solano, mixer,\n",
      "Nearest to i: we, you, they, ii, iii, g, UNK, epidemic,\n",
      "Nearest to many: some, several, various, most, all, numerous, those, resettle,\n",
      "Nearest to had: has, have, having, was, were, never, vr, gave,\n",
      "Nearest to war: symphonies, folds, diarist, chapter, saboteurs, coventry, mongols, wars,\n",
      "Nearest to nine: eight, seven, six, four, five, three, zero, about,\n",
      "Nearest to known: used, described, defined, regarded, such, seen, interned, decoction,\n",
      "Nearest to six: five, eight, seven, four, nine, three, zero, two,\n",
      "Nearest to there: they, it, he, she, usually, often, still, tren,\n",
      "Nearest to when: if, before, after, while, though, where, although, during,\n",
      "Average loss at step 42000: 2.946611\n",
      "Average loss at step 44000: 2.960336\n",
      "Average loss at step 46000: 2.907013\n",
      "Average loss at step 48000: 2.862791\n",
      "Average loss at step 50000: 2.847541\n",
      "Nearest to for: against, including, after, tlp, when, if, emblazoned, zealot,\n",
      "Nearest to its: their, his, her, our, the, your, whose, washes,\n",
      "Nearest to about: mourned, machinima, making, mau, fela, distal, intervocalic, compatibility,\n",
      "Nearest to four: six, five, seven, eight, three, nine, two, zero,\n",
      "Nearest to people: children, men, christians, women, those, players, authors, individuals,\n",
      "Nearest to all: many, various, both, every, alga, those, some, investments,\n",
      "Nearest to system: systems, program, unisys, unit, lonsdaleite, mixer, vga, units,\n",
      "Nearest to i: we, you, ii, iii, g, coleco, bipedal, rent,\n",
      "Nearest to many: several, some, various, these, most, all, those, numerous,\n",
      "Nearest to had: has, have, having, was, were, knew, since, never,\n",
      "Nearest to war: wars, symphonies, chulainn, lyon, diarist, saboteurs, winged, coventry,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, two,\n",
      "Nearest to known: used, described, regarded, such, defined, available, called, decoction,\n",
      "Nearest to six: seven, four, eight, five, nine, three, zero, two,\n",
      "Nearest to there: they, it, he, usually, often, she, squaw, tren,\n",
      "Nearest to when: if, before, after, while, where, during, although, because,\n",
      "Average loss at step 52000: 2.891003\n",
      "Average loss at step 54000: 2.866952\n",
      "Average loss at step 56000: 2.854764\n",
      "Average loss at step 58000: 2.750682\n",
      "Average loss at step 60000: 2.832382\n",
      "Nearest to for: without, emblazoned, hardens, when, after, against, peg, fein,\n",
      "Nearest to its: their, his, our, the, her, whose, your, washes,\n",
      "Nearest to about: mau, mourned, regarding, subtitling, mammuthus, ec, boil, making,\n",
      "Nearest to four: six, five, seven, three, eight, two, nine, one,\n",
      "Nearest to people: children, christians, men, authors, americans, individuals, women, players,\n",
      "Nearest to all: various, many, both, those, every, these, each, several,\n",
      "Nearest to system: systems, program, unisys, lonsdaleite, situation, unit, process, trask,\n",
      "Nearest to i: you, we, matchup, bipedal, ii, iii, everyone, rips,\n",
      "Nearest to many: several, some, various, those, numerous, all, these, most,\n",
      "Nearest to had: has, have, was, were, having, wanted, gave, never,\n",
      "Nearest to war: wars, symphonies, diarist, saboteurs, folds, chulainn, temmu, winged,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, one,\n",
      "Nearest to known: used, defined, described, such, regarded, called, seen, possible,\n",
      "Nearest to six: five, seven, four, eight, nine, three, two, zero,\n",
      "Nearest to there: they, it, he, she, tren, squaw, usually, often,\n",
      "Nearest to when: if, while, although, where, before, though, after, during,\n",
      "Average loss at step 62000: 2.832618\n",
      "Average loss at step 64000: 2.772800\n",
      "Average loss at step 66000: 2.763977\n",
      "Average loss at step 68000: 2.710855\n",
      "Average loss at step 70000: 2.791403\n",
      "Nearest to for: hardens, after, including, against, fein, grievous, emblazoned, monocotyledons,\n",
      "Nearest to its: their, his, the, her, our, whose, bornholm, washes,\n",
      "Nearest to about: mau, regarding, making, subtitling, mourned, arnulf, seismology, fela,\n",
      "Nearest to four: seven, six, three, five, eight, two, nine, zero,\n",
      "Nearest to people: children, americans, women, men, authors, individuals, jews, christians,\n",
      "Nearest to all: both, various, many, every, each, those, some, csa,\n",
      "Nearest to system: systems, program, unisys, lonsdaleite, unit, process, cmb, domain,\n",
      "Nearest to i: you, we, ii, iii, iv, annihilate, regan, tougher,\n",
      "Nearest to many: some, several, various, numerous, all, both, these, most,\n",
      "Nearest to had: has, have, having, was, were, wanted, sayfawa, popcorn,\n",
      "Nearest to war: wars, conflict, flores, saboteurs, symphonies, chulainn, winged, diarist,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, two,\n",
      "Nearest to known: defined, described, such, used, possible, regarded, called, available,\n",
      "Nearest to six: eight, seven, five, nine, four, three, zero, two,\n",
      "Nearest to there: they, it, he, we, she, still, often, where,\n",
      "Nearest to when: if, while, before, though, although, after, where, during,\n",
      "Average loss at step 72000: 2.799699\n",
      "Average loss at step 74000: 2.639454\n",
      "Average loss at step 76000: 2.795481\n",
      "Average loss at step 78000: 2.820740\n",
      "Average loss at step 80000: 2.784196\n",
      "Nearest to for: including, after, when, hardens, while, during, peg, without,\n",
      "Nearest to its: their, his, her, our, the, whose, inclusive, revenue,\n",
      "Nearest to about: mau, mourned, making, regarding, morrie, widest, dmu, influencing,\n",
      "Nearest to four: five, seven, six, three, eight, two, nine, zero,\n",
      "Nearest to people: children, women, americans, authors, men, persons, individuals, jews,\n",
      "Nearest to all: both, various, many, any, several, every, csa, notions,\n",
      "Nearest to system: systems, unisys, program, unit, situation, process, clutter, lonsdaleite,\n",
      "Nearest to i: you, we, ii, they, everyone, iii, annihilate, shabbat,\n",
      "Nearest to many: several, some, various, numerous, most, both, all, these,\n",
      "Nearest to had: has, have, having, was, were, finer, ever, never,\n",
      "Nearest to war: wars, flores, winged, crete, mongols, conflict, saboteurs, macau,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, two,\n",
      "Nearest to known: used, possible, defined, described, regarded, such, referred, understood,\n",
      "Nearest to six: seven, five, eight, nine, four, three, zero, two,\n",
      "Nearest to there: they, it, he, she, we, often, sometimes, believed,\n",
      "Nearest to when: if, although, while, though, after, during, where, before,\n",
      "Average loss at step 82000: 2.663811\n",
      "Average loss at step 84000: 2.772719\n",
      "Average loss at step 86000: 2.734643\n",
      "Average loss at step 88000: 2.752059\n",
      "Average loss at step 90000: 2.738620\n",
      "Nearest to for: hardens, when, including, creole, emblazoned, after, although, conservancy,\n",
      "Nearest to its: their, his, the, whose, her, our, washes, ursa,\n",
      "Nearest to about: regarding, bjelke, africana, gospels, over, mourned, around, subtitling,\n",
      "Nearest to four: six, seven, five, eight, three, nine, two, zero,\n",
      "Nearest to people: children, women, americans, men, individuals, christians, persons, jews,\n",
      "Nearest to all: both, various, many, any, those, most, every, bounded,\n",
      "Nearest to system: systems, unisys, situation, process, unit, lonsdaleite, program, period,\n",
      "Nearest to i: we, you, they, iii, ii, iv, annihilate, bessel,\n",
      "Nearest to many: some, several, various, numerous, most, those, both, all,\n",
      "Nearest to had: has, have, having, was, were, wanted, tended, saw,\n",
      "Nearest to war: wars, conflict, winged, diarist, mongols, flores, saboteurs, edo,\n",
      "Nearest to nine: eight, seven, six, four, five, three, zero, two,\n",
      "Nearest to known: used, defined, regarded, described, possible, intended, referred, such,\n",
      "Nearest to six: seven, eight, four, nine, five, three, zero, two,\n",
      "Nearest to there: they, she, it, he, we, disjoint, still, now,\n",
      "Nearest to when: if, although, before, while, after, though, where, dione,\n",
      "Average loss at step 92000: 2.676654\n",
      "Average loss at step 94000: 2.722155\n",
      "Average loss at step 96000: 2.699170\n",
      "Average loss at step 98000: 2.370708\n",
      "Average loss at step 100000: 2.400822\n",
      "Nearest to for: after, against, malo, hardens, as, intersecting, without, by,\n",
      "Nearest to its: their, his, her, our, the, whose, dde, bornholm,\n",
      "Nearest to about: morrie, bjelke, regarding, africana, gospels, hamdi, around, efta,\n",
      "Nearest to four: six, seven, five, eight, three, nine, zero, two,\n",
      "Nearest to people: children, women, men, individuals, jews, persons, americans, citizens,\n",
      "Nearest to all: various, both, those, several, many, every, some, any,\n",
      "Nearest to system: systems, unit, unisys, lonsdaleite, process, program, clutter, units,\n",
      "Nearest to i: you, we, ii, iii, iv, they, boson, bum,\n",
      "Nearest to many: several, some, numerous, various, those, all, viz, both,\n",
      "Nearest to had: has, have, having, was, since, never, were, saw,\n",
      "Nearest to war: wars, conflict, crete, macau, mongols, statism, lyon, raisins,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, two,\n",
      "Nearest to known: defined, used, regarded, described, available, possible, such, understood,\n",
      "Nearest to six: four, eight, nine, seven, five, three, zero, two,\n",
      "Nearest to there: they, she, he, it, here, we, still, usually,\n",
      "Nearest to when: if, while, before, where, after, though, although, dione,\n"
     ]
    }
   ],
   "source": [
    "num_steps = 100001\n",
    "\n",
    "with tf.Session(graph=graph) as session:\n",
    "  tf.initialize_all_variables().run()\n",
    "  print('Initialized')\n",
    "  average_loss = 0\n",
    "  for step in range(num_steps):\n",
    "    batch_data, batch_labels = generate_cbow_batch(\n",
    "      batch_size, skip_window)\n",
    "    feed_dict = {train_dataset : batch_data, train_labels : batch_labels}\n",
    "    _, l = session.run([optimizer, loss], feed_dict=feed_dict)\n",
    "    average_loss += l\n",
    "    if step % 2000 == 0:\n",
    "      if step > 0:\n",
    "        average_loss = average_loss / 2000\n",
    "      # The average loss is an estimate of the loss over the last 2000 batches.\n",
    "      print('Average loss at step %d: %f' % (step, average_loss))\n",
    "      average_loss = 0\n",
    "    # note that this is expensive (~20% slowdown if computed every 500 steps)\n",
    "    if step % 10000 == 0:\n",
    "      sim = similarity.eval()\n",
    "      for i in range(valid_size):\n",
    "        valid_word = reverse_dictionary[valid_examples[i]]\n",
    "        top_k = 8 # number of nearest neighbors\n",
    "        nearest = (-sim[i, :]).argsort()[1:top_k+1]\n",
    "        log = 'Nearest to %s:' % valid_word\n",
    "        for k in range(top_k):\n",
    "          close_word = reverse_dictionary[nearest[k]]\n",
    "          log = '%s %s,' % (log, close_word)\n",
    "        print(log)\n",
    "  final_embeddings = normalized_embeddings.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "num_points = 400\n",
    "\n",
    "tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=5000)\n",
    "two_d_embeddings = tsne.fit_transform(final_embeddings[1:num_points+1, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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blpKSUt7NFRERKTcK5EREysH58+fp27cvfn5+eHt7s2bNGowxLFiwgA4dOuDj42NLznHq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x48cpIiJCytA+NTWV2rZtS0ZGRnTnzp16619tDezfR0MNiGqDxPalusmhhrwfR0ZGkqen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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe996841cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot(embeddings, labels):\n",
    "  assert embeddings.shape[0] >= len(labels), 'More labels than embeddings'\n",
    "  pylab.figure(figsize=(15,15))  # in inches\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',\n",
    "                   ha='right', va='bottom')\n",
    "  pylab.show()\n",
    "\n",
    "words = [reverse_dictionary[i] for i in range(1, num_points+1)]\n",
    "plot(two_d_embeddings, words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "default_view": {},
   "name": "5_word2vec.ipynb",
   "provenance": [],
   "version": "0.3.2",
   "views": {}
  },
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}