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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    "id": "aCjPJE944bkV"
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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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     "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": {
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   "source": [
    "Build the dictionary and replace rare words with UNK token."
   ]
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     "text": [
      "{}\n"
     ]
    }
   ],
   "source": [
    "a = dict()\n",
    "print(a)"
   ]
  },
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     "text": [
      "Most common words (+UNK) [['UNK', 418391], ('the', 1061396), ('of', 593677), ('and', 416629), ('one', 411764)]\n",
      "Sample data [5244, 3081, 12, 6, 195, 2, 3136, 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",
    "\n",
    "del words  # Hint to reduce memory."
   ]
  },
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   "source": [
    "Function to generate a training batch for the skip-gram model."
   ]
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     "text": [
      "data: ['anarchism', 'originated', 'as', 'a', 'term', 'of', 'abuse', 'first']\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', 'term', 'as', 'a', 'of']\n",
      "\n",
      "with num_skips = 4 and skip_window = 2:\n",
      "    batch: ['as', 'as', 'as', 'as', 'a', 'a', 'a', 'a']\n",
      "    labels: ['originated', 'a', 'term', 'anarchism', 'as', 'term', 'originated', 'of']\n"
     ]
    }
   ],
   "source": [
    "data_index = 0\n",
    "\n",
    "def generate_batch(batch_size, num_skips, skip_window):\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[:8]])\n",
    "\n",
    "for num_skips, skip_window in [(2, 1), (4, 2)]:\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": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ofd1MbBuwiva"
   },
   "source": [
    "Train a skip-gram model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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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",
    "  # Note: The optimizer will optimize the softmax_weights AND the embeddings.\n",
    "  # This is because the embeddings are defined as a variable quantity and the\n",
    "  # optimizer's `minimize` method will by default modify all variable quantities \n",
    "  # that contribute to the tensor it is passed.\n",
    "  # See docs on `tf.train.Optimizer.minimize()` for more details.\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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     "text": [
      "Initialized\n",
      "Average loss at step 0: 8.178864\n",
      "Nearest to three: blues, monies, powiat, climber, besieged, fortunate, feasibility, reconstructionist,\n",
      "Nearest to if: konkan, kickoff, anechoic, cameos, lives, boer, overuse, monstrous,\n",
      "Nearest to a: shel, pka, planck, ltcm, belloc, boulevard, focused, conceiving,\n",
      "Nearest to united: hydroponics, chakra, sinister, insurance, inextricably, kidnap, depressive, soleil,\n",
      "Nearest to often: afford, hotel, pedestal, rams, reviews, barnet, uart, megatokyo,\n",
      "Nearest to they: solidly, mora, dinosauria, later, chapelle, scavenge, corning, dunant,\n",
      "Nearest to one: unison, felt, ferenc, stood, rubin, corning, crystallizes, atahualpa,\n",
      "Nearest to he: additionally, looters, mubarak, barbosa, rewriting, writings, willful, yetzer,\n",
      "Nearest to no: superstars, rolle, inasmuch, transuranic, seriousness, gojira, ruud, takeoff,\n",
      "Nearest to be: unforgettable, spivak, prostaglandin, ezekiel, eyeglasses, remove, arr, stave,\n",
      "Nearest to such: carnarvon, pyongyang, counts, happier, rich, specialty, spitz, purify,\n",
      "Nearest to most: steadfastly, pohl, turnpike, geostationary, gielgud, corrado, pigpen, reconstruction,\n",
      "Nearest to history: divides, petition, appropriate, containers, theologies, tincture, axis, entity,\n",
      "Nearest to their: tort, eros, gotham, viewed, cycladic, riddle, premature, soulful,\n",
      "Nearest to but: donatello, bloemfontein, voiceover, decolonisation, inductive, eden, maximian, lugs,\n",
      "Nearest to nine: hmos, postalveolar, oblast, lighters, szabo, envision, endymion, tba,\n",
      "Average loss at step 2000: 4.353458\n",
      "Average loss at step 4000: 3.867660\n",
      "Average loss at step 6000: 3.782074\n",
      "Average loss at step 8000: 3.690021\n",
      "Average loss at step 10000: 3.618049\n",
      "Nearest to three: eight, five, four, six, seven, two, nine, zero,\n",
      "Nearest to if: krahn, kristen, cossacks, anechoic, konkan, committed, via, beheaded,\n",
      "Nearest to a: the, boulevard, this, shel, collectively, ingesting, nfs, his,\n",
      "Nearest to united: chakra, hydroponics, djing, insurance, soleil, product, verify, fuss,\n",
      "Nearest to often: equals, unambiguously, sometimes, not, barnet, conservationist, arius, also,\n",
      "Nearest to they: he, not, there, it, mora, later, drenched, byron,\n",
      "Nearest to one: two, three, five, seven, six, eight, four, assurance,\n",
      "Nearest to he: it, they, she, who, there, chronology, and, authenticity,\n",
      "Nearest to no: magnetization, it, vives, polonium, meritocratic, concubine, ethics, rolle,\n",
      "Nearest to be: have, is, was, been, are, nixon, by, pervasive,\n",
      "Nearest to such: well, beatle, pyongyang, counts, feldman, traditions, persistent, psychoactive,\n",
      "Nearest to most: turnpike, pigpen, use, steadfastly, lingered, nueva, geostationary, all,\n",
      "Nearest to history: petition, ebbets, divides, aloof, axis, resultant, containers, jumped,\n",
      "Nearest to their: his, the, its, riddle, syria, szab, gotham, tort,\n",
      "Nearest to but: tuesday, finds, erupting, donatello, she, medication, grudge, tauris,\n",
      "Nearest to nine: eight, seven, six, five, three, zero, four, two,\n",
      "Average loss at step 12000: 3.606861\n",
      "Average loss at step 14000: 3.570593\n",
      "Average loss at step 16000: 3.407310\n",
      "Average loss at step 18000: 3.464861\n",
      "Average loss at step 20000: 3.540145\n",
      "Nearest to three: six, seven, four, two, eight, five, zero, nine,\n",
      "Nearest to if: when, krahn, cossacks, should, kristen, since, showed, via,\n",
      "Nearest to a: shel, this, the, granville, collectively, boulevard, any, gabal,\n",
      "Nearest to united: chakra, hydroponics, djing, soleil, insurance, diedrich, renting, diner,\n",
      "Nearest to often: sometimes, equals, also, it, barnet, conservationist, generally, unambiguously,\n",
      "Nearest to they: he, we, there, it, you, not, who, drenched,\n",
      "Nearest to one: two, four, six, three, seven, eight, nine, five,\n",
      "Nearest to he: it, she, they, who, there, whorf, which, later,\n",
      "Nearest to no: vives, or, medline, any, entre, not, yang, butyl,\n",
      "Nearest to be: have, been, is, penfield, become, was, by, are,\n",
      "Nearest to such: well, beatle, many, these, feldman, lange, special, glassware,\n",
      "Nearest to most: use, pigpen, more, all, many, turnpike, some, nueva,\n",
      "Nearest to history: petition, chromic, divides, theories, cliffordadams, computer, tackle, xbox,\n",
      "Nearest to their: his, its, the, her, these, some, riichi, many,\n",
      "Nearest to but: although, however, which, and, though, that, would, vignettes,\n",
      "Nearest to nine: eight, seven, six, four, five, three, zero, two,\n",
      "Average loss at step 22000: 3.500046\n",
      "Average loss at step 24000: 3.488270\n",
      "Average loss at step 26000: 3.486683\n",
      "Average loss at step 28000: 3.479520\n",
      "Average loss at step 30000: 3.500391\n",
      "Nearest to three: five, four, seven, eight, six, two, zero, nine,\n",
      "Nearest to if: when, where, minimalist, should, since, but, showed, halpin,\n",
      "Nearest to a: any, no, ltcm, jardines, shel, every, suggestibility, deutschen,\n",
      "Nearest to united: chakra, djing, hydroponics, insurance, diedrich, soleil, infrastructures, sinister,\n",
      "Nearest to often: sometimes, generally, also, there, still, unambiguously, conservationist, usually,\n",
      "Nearest to they: we, he, there, you, who, not, it, these,\n",
      "Nearest to one: two, four, seven, eight, five, three, six, nine,\n",
      "Nearest to he: she, it, they, who, there, whorf, authenticity, tighter,\n",
      "Nearest to no: any, vives, still, a, polonium, medline, battista, butyl,\n",
      "Nearest to be: been, have, is, become, penfield, pervasive, partnering, was,\n",
      "Nearest to such: well, these, known, like, many, feldman, some, romanorum,\n",
      "Nearest to most: more, use, pigpen, many, some, apostol, nueva, turnpike,\n",
      "Nearest to history: library, theories, huddle, xbox, chromic, aloof, axis, divides,\n",
      "Nearest to their: his, its, the, her, these, many, some, riichi,\n",
      "Nearest to but: however, although, while, and, that, which, though, he,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, births,\n",
      "Average loss at step 32000: 3.501715\n",
      "Average loss at step 34000: 3.488674\n",
      "Average loss at step 36000: 3.456981\n",
      "Average loss at step 38000: 3.300279\n",
      "Average loss at step 40000: 3.431831\n",
      "Nearest to three: four, five, seven, six, two, eight, nine, zero,\n",
      "Nearest to if: when, where, is, disguises, because, minimalist, governorship, scalp,\n",
      "Nearest to a: the, any, another, no, shel, or, granville, innovators,\n",
      "Nearest to united: chakra, djing, hydroponics, diedrich, diner, infrastructures, mysia, southern,\n",
      "Nearest to often: sometimes, generally, usually, also, still, commonly, there, frequently,\n",
      "Nearest to they: we, you, he, there, it, who, she, not,\n",
      "Nearest to one: seven, four, eight, two, six, five, three, nine,\n",
      "Nearest to he: it, she, they, who, there, later, i, tighter,\n",
      "Nearest to no: any, or, a, vives, still, medline, magnetization, malignancies,\n",
      "Nearest to be: been, have, were, was, is, become, are, being,\n",
      "Nearest to such: well, these, known, saskatoon, superhero, many, beatle, gb,\n",
      "Nearest to most: more, many, pigpen, reconstruction, use, apostol, some, togo,\n",
      "Nearest to history: sums, ebbets, ecuadorean, tenacity, form, unfit, axis, theories,\n",
      "Nearest to their: its, his, her, the, riichi, your, these, some,\n",
      "Nearest to but: however, although, while, which, and, though, where, when,\n",
      "Nearest to nine: eight, seven, six, five, four, zero, three, one,\n",
      "Average loss at step 42000: 3.438282\n",
      "Average loss at step 44000: 3.452140\n",
      "Average loss at step 46000: 3.452459\n",
      "Average loss at step 48000: 3.353163\n",
      "Average loss at step 50000: 3.383526\n",
      "Nearest to three: six, four, seven, eight, five, nine, two, zero,\n",
      "Nearest to if: when, where, before, since, scalp, although, should, disguises,\n",
      "Nearest to a: the, another, any, shel, failures, boulevard, no, roden,\n",
      "Nearest to united: djing, chakra, hydroponics, infrastructures, syrian, southern, mysia, diedrich,\n",
      "Nearest to often: sometimes, generally, usually, commonly, still, frequently, also, now,\n",
      "Nearest to they: he, we, there, you, it, she, these, who,\n",
      "Nearest to one: two, six, four, eight, three, seven, five, nine,\n",
      "Nearest to he: she, it, they, there, who, whorf, nuit, nuova,\n",
      "Nearest to no: any, a, sentry, consorts, battista, simulators, magnetization, chieftain,\n",
      "Nearest to be: were, been, have, was, is, are, become, partnering,\n",
      "Nearest to such: well, these, many, known, superhero, equivocation, saskatoon, intrauterine,\n",
      "Nearest to most: more, many, reconstruction, less, use, apostol, pigpen, turnpike,\n",
      "Nearest to history: sums, unfit, mems, span, maxima, ecuadorean, tenacity, mosque,\n",
      "Nearest to their: its, his, her, the, mysore, our, these, your,\n",
      "Nearest to but: however, although, though, while, and, where, when, since,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, one,\n",
      "Average loss at step 52000: 3.433182\n",
      "Average loss at step 54000: 3.428478\n",
      "Average loss at step 56000: 3.437756\n",
      "Average loss at step 58000: 3.394547\n",
      "Average loss at step 60000: 3.391157\n",
      "Nearest to three: five, four, six, eight, two, seven, nine, zero,\n",
      "Nearest to if: when, where, before, though, because, since, should, so,\n",
      "Nearest to a: any, the, another, every, innovators, shel, no, ingesting,\n",
      "Nearest to united: chakra, djing, hydroponics, syrian, infrastructures, medley, diedrich, mysia,\n",
      "Nearest to often: sometimes, usually, generally, commonly, frequently, still, also, now,\n",
      "Nearest to they: we, you, there, he, she, these, it, i,\n",
      "Nearest to one: four, two, six, eight, seven, five, three, nine,\n",
      "Nearest to he: she, it, they, there, whorf, who, nuova, we,\n",
      "Nearest to no: any, consorts, a, little, chieftain, kearney, vous, codes,\n",
      "Nearest to be: been, have, is, become, were, partnering, erlang, are,\n",
      "Nearest to such: well, these, known, many, superhero, including, saskatoon, intrauterine,\n",
      "Nearest to most: more, many, some, less, use, reconstruction, pigpen, all,\n",
      "Nearest to history: list, politics, ecuadorean, huddle, antagonist, corvettes, movements, rights,\n",
      "Nearest to their: its, his, her, the, our, whose, demographic, your,\n",
      "Nearest to but: however, although, and, though, which, while, see, when,\n",
      "Nearest to nine: eight, six, seven, five, four, three, zero, one,\n",
      "Average loss at step 62000: 3.234124\n",
      "Average loss at step 64000: 3.254733\n",
      "Average loss at step 66000: 3.401987\n",
      "Average loss at step 68000: 3.392400\n",
      "Average loss at step 70000: 3.354513\n",
      "Nearest to three: four, six, five, seven, two, eight, nine, zero,\n",
      "Nearest to if: when, though, where, before, since, while, because, should,\n",
      "Nearest to a: the, another, any, twinning, shel, every, psalter, amounts,\n",
      "Nearest to united: chakra, djing, hydroponics, syrian, infrastructures, following, tamerlane, diner,\n",
      "Nearest to often: sometimes, usually, generally, commonly, frequently, also, now, still,\n",
      "Nearest to they: we, he, there, you, she, it, actually, these,\n",
      "Nearest to one: six, two, seven, four, five, eight, three, nine,\n",
      "Nearest to he: she, it, they, who, there, whorf, nuova, we,\n",
      "Nearest to no: any, consorts, little, there, beaked, sentry, codes, demeter,\n",
      "Nearest to be: been, become, were, is, are, have, being, partnering,\n",
      "Nearest to such: well, these, known, superhero, many, equivocation, separate, generalization,\n",
      "Nearest to most: more, many, less, reconstruction, some, quartering, lingered, steadfastly,\n",
      "Nearest to history: list, biblical, assassination, redesignated, nolan, corvettes, hbk, ecuadorean,\n",
      "Nearest to their: its, his, her, the, our, some, your, these,\n",
      "Nearest to but: however, although, though, which, that, and, actually, while,\n",
      "Nearest to nine: eight, six, seven, four, five, three, zero, two,\n",
      "Average loss at step 72000: 3.374199\n",
      "Average loss at step 74000: 3.350004\n",
      "Average loss at step 76000: 3.312426\n",
      "Average loss at step 78000: 3.347111\n",
      "Average loss at step 80000: 3.376940\n",
      "Nearest to three: four, five, six, seven, two, eight, zero, nine,\n",
      "Nearest to if: when, though, before, since, where, because, did, should,\n",
      "Nearest to a: the, every, another, roden, operators, deutschen, shel, gabal,\n",
      "Nearest to united: chakra, djing, hydroponics, infrastructures, syrian, forbade, athletic, confining,\n",
      "Nearest to often: sometimes, usually, generally, commonly, frequently, still, now, rarely,\n",
      "Nearest to they: we, he, there, you, she, it, these, actually,\n",
      "Nearest to one: seven, six, two, eight, four, three, five, nine,\n",
      "Nearest to he: she, it, they, there, who, nuova, we, browed,\n",
      "Nearest to no: little, any, sentry, consorts, beaked, codes, bested, mithra,\n",
      "Nearest to be: been, become, have, partnering, being, were, refer, nanda,\n",
      "Nearest to such: well, these, known, superhero, certain, including, defined, separate,\n",
      "Nearest to most: more, many, less, reconstruction, some, among, apostol, especially,\n",
      "Nearest to history: list, hbk, emperors, nightmare, corvettes, ecuadorean, tenacity, historical,\n",
      "Nearest to their: its, his, her, our, your, the, whose, these,\n",
      "Nearest to but: however, although, though, while, and, see, mecha, or,\n",
      "Nearest to nine: eight, seven, six, five, four, three, zero, births,\n",
      "Average loss at step 82000: 3.410170\n",
      "Average loss at step 84000: 3.409590\n",
      "Average loss at step 86000: 3.392083\n",
      "Average loss at step 88000: 3.350390\n",
      "Average loss at step 90000: 3.363069\n",
      "Nearest to three: four, five, two, seven, six, eight, nine, zero,\n",
      "Nearest to if: when, since, though, before, where, after, refuted, scalp,\n",
      "Nearest to a: roden, every, another, woogie, any, the, ltcm, caplan,\n",
      "Nearest to united: chakra, djing, following, constitution, hydroponics, infrastructures, syrian, tenth,\n",
      "Nearest to often: sometimes, usually, generally, commonly, frequently, still, now, rarely,\n",
      "Nearest to they: we, he, there, you, she, it, not, who,\n",
      "Nearest to one: seven, four, two, eight, six, five, three, nine,\n",
      "Nearest to he: she, it, they, there, who, whorf, browed, later,\n",
      "Nearest to no: little, any, specimen, only, sentry, undeniable, characterizing, codes,\n",
      "Nearest to be: been, become, have, is, was, refer, being, zubaydah,\n",
      "Nearest to such: well, known, these, superhero, certain, many, separate, opposed,\n",
      "Nearest to most: more, less, many, some, among, reconstruction, particularly, especially,\n",
      "Nearest to history: list, hbk, nightmare, mormon, huddle, ezquerra, krs, corvettes,\n",
      "Nearest to their: his, its, her, our, your, the, whose, some,\n",
      "Nearest to but: however, although, and, though, while, honecker, he, which,\n",
      "Nearest to nine: seven, eight, six, five, four, zero, three, births,\n",
      "Average loss at step 92000: 3.398418\n",
      "Average loss at step 94000: 3.253503\n",
      "Average loss at step 96000: 3.354896\n",
      "Average loss at step 98000: 3.242361\n",
      "Average loss at step 100000: 3.354259\n",
      "Nearest to three: four, five, seven, six, eight, two, nine, zero,\n",
      "Nearest to if: when, though, before, since, where, while, so, after,\n",
      "Nearest to a: another, any, the, roden, gabal, ltcm, woogie, shel,\n",
      "Nearest to united: chakra, djing, infrastructures, following, hydroponics, constitution, tenth, syrian,\n",
      "Nearest to often: usually, sometimes, generally, commonly, frequently, rarely, typically, actually,\n",
      "Nearest to they: we, he, there, you, she, it, i, not,\n",
      "Nearest to one: two, four, six, seven, five, eight, nine, three,\n",
      "Nearest to he: she, it, they, there, we, who, never, whorf,\n",
      "Nearest to no: any, little, only, codes, advocacy, sentry, there, chill,\n",
      "Nearest to be: been, become, have, partnering, refer, erlang, being, is,\n",
      "Nearest to such: well, known, these, superhero, separate, certain, many, opposed,\n",
      "Nearest to most: more, less, especially, reconstruction, apostol, among, many, particularly,\n",
      "Nearest to history: list, hbk, nightmare, span, biblical, ezquerra, moselle, courtenay,\n",
      "Nearest to their: its, his, her, our, your, the, these, whose,\n",
      "Nearest to but: however, although, and, though, while, when, where, gator,\n",
      "Nearest to nine: eight, seven, six, four, five, three, zero, one,\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",
    "    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": 14,
   "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": 15,
   "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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CFATWzMxLA6vWsxS5uSjIiZRDAwcOZODAgRfcd3HJb7i0qtuVSoRfvL7Tu+++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\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1abfl13laW1vj/PnzePz4McrKyrBv3z44OjrWt5lvRJUdJSbo8WZYn6X5w/LIMZoVFdXW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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f7cf908>"
      ]
     },
     "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": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data: ['anarchism', 'originated', 'as', 'a', 'term', 'of', 'abuse', 'first']\n",
      "\n",
      "with num_cbows = 2 and cbow_window = 1:\n",
      "    batch: [['anarchism', 'as'], ['originated', 'a'], ['term', 'as'], ['of', 'a']]\n",
      "    labels: ['originated', 'as', 'a', 'term']\n",
      "\n",
      "with num_cbows = 4 and cbow_window = 2:\n",
      "    batch: [['originated', 'term', 'anarchism', 'a'], ['as', 'term', 'of', 'originated']]\n",
      "    labels: ['as', 'a']\n"
     ]
    }
   ],
   "source": [
    "data_index = 0\n",
    "\n",
    "def generate_cbow_batch(batch_size, num_cbows, cbow_window):\n",
    "  global data_index\n",
    "  assert batch_size % num_cbows == 0\n",
    "  assert num_cbows <= 2 * cbow_window\n",
    "  # for convinience, batch_size here actually is the size of batch.flatten()\n",
    "  flat_batch = np.ndarray(shape=(batch_size), dtype=np.int32)\n",
    "  labels = np.ndarray(shape=(batch_size//num_cbows, 1), dtype=np.int32)\n",
    "  span = 2 * cbow_window + 1 # [ cbow_window target cbow_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_cbows):\n",
    "    target = cbow_window  # target label at the center of the buffer\n",
    "    targets_to_avoid = [ cbow_window ]\n",
    "    for j in range(num_cbows):\n",
    "      while target in targets_to_avoid:\n",
    "        target = random.randint(0, span - 1)\n",
    "      targets_to_avoid.append(target)\n",
    "      flat_batch[i * num_cbows + j] = buffer[target]\n",
    "    labels[i, 0] = buffer[cbow_window]\n",
    "    buffer.append(data[data_index])\n",
    "    data_index = (data_index + 1) % len(data)\n",
    "    batch = flat_batch.reshape((-1,num_cbows))\n",
    "  return batch, labels\n",
    "\n",
    "print('data:', [reverse_dictionary[di] for di in data[:8]])\n",
    "\n",
    "for num_cbows, cbow_window in [(2, 1), (4, 2)]:\n",
    "    data_index = 0\n",
    "    batch, labels = generate_cbow_batch(batch_size=8, num_cbows=num_cbows, cbow_window=cbow_window)\n",
    "    print('\\nwith num_cbows = %d and cbow_window = %d:' % (num_cbows, cbow_window))\n",
    "    \n",
    "    print('    batch:', [[reverse_dictionary[bij] for bij in bi] for bi in batch])\n",
    "    print('    labels:', [reverse_dictionary[li] for li in labels.reshape(8//num_cbows)])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "batch_size = 128\n",
    "embedding_size = 128 # Dimension of the embedding vector.\n",
    "cbow_window = 2 # How many words to consider left and right.\n",
    "num_cbows = 4 # 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",
    "  train_dataset = tf.placeholder(tf.int32, shape=[batch_size//num_cbows,num_cbows])\n",
    "  train_labels = tf.placeholder(tf.int32, shape=[batch_size//num_cbows, 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.reduce_sum(tf.nn.embedding_lookup(embeddings, train_dataset), [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",
    "  # Note: The optimizer will optimize the softmax_weights AND the embeddings.\n",
    "  # This is because the embeddings are defined as a variable quantity and the\n",
    "  # optimizer's `minimize` method will by default modify all variable quantities \n",
    "  # that contribute to the tensor it is passed.\n",
    "  # See docs on `tf.train.Optimizer.minimize()` for more details.\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": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialized\n",
      "Average loss at step 0: 7.925443\n",
      "Nearest to over: lysander, christiane, serbians, globalization, polarization, kuznetsov, shootings, civilised,\n",
      "Nearest to known: tumult, leans, eia, breeder, josephus, unifil, rita, plaster,\n",
      "Nearest to may: seduce, lurking, acapulco, marijuana, therefore, amazing, durban, hohmann,\n",
      "Nearest to after: emissary, davids, brummell, milder, aggressors, besieging, marr, recipients,\n",
      "Nearest to at: granules, elohim, frida, cockburn, aggregate, ladders, fide, scum,\n",
      "Nearest to more: giacomo, fried, projective, frs, regional, mccann, favourites, scot,\n",
      "Nearest to only: strasberg, leroy, microsoft, orfeo, chipsets, removing, baur, lives,\n",
      "Nearest to from: holliday, instituted, irl, uplink, upholding, psilocybin, shura, tricking,\n",
      "Nearest to four: minimalism, endian, majuro, hosted, sage, sheltered, coherent, wrongdoing,\n",
      "Nearest to b: phil, dafoe, harpercollins, catania, pan, concessions, vanilla, cmd,\n",
      "Nearest to will: inauguration, explained, accomplice, corporal, fable, encoder, cynic, fluorine,\n",
      "Nearest to seven: sustains, psychotherapist, carriers, sphincter, algardi, plaintiff, slew, gent,\n",
      "Nearest to one: tien, damping, grampus, outbound, sampa, titular, pacemakers, antecedent,\n",
      "Nearest to UNK: eliminates, punic, diversions, pepys, engined, origins, continues, ovulation,\n",
      "Nearest to on: rifled, noaa, milwaukee, le, officiated, captive, shores, durian,\n",
      "Nearest to into: yarmouth, ambrose, um, coens, excerpted, lactation, fujitsu, cours,\n",
      "Average loss at step 2000: 6.185424\n",
      "Average loss at step 4000: 5.319203\n",
      "Average loss at step 6000: 5.151704\n",
      "Average loss at step 8000: 5.074501\n",
      "Average loss at step 10000: 4.899031\n",
      "Nearest to over: latour, wmd, ecologically, girl, isadora, ratzinger, decide, unravel,\n",
      "Nearest to known: clyde, referred, inauguration, adm, systems, used, awarding, misspelled,\n",
      "Nearest to may: could, can, should, will, cannot, would, iho, appears,\n",
      "Nearest to after: earthworm, formally, at, mt, erebus, ii, dinosaur, heteronyms,\n",
      "Nearest to at: overwhelmingly, on, after, europeans, volcano, ross, dolphin, importing,\n",
      "Nearest to more: kal, less, hacking, jewry, engagement, sixties, gravy, wolfman,\n",
      "Nearest to only: mt, active, formally, angola, aircraft, declared, dung, island,\n",
      "Nearest to from: frieze, between, bara, within, arguable, quicktime, laches, kale,\n",
      "Nearest to four: ovaries, nine, classified, amethyst, seven, landslide, inconceivable, coolidge,\n",
      "Nearest to b: mafia, geometries, lillehammer, rate, outputting, breda, brooke, mashal,\n",
      "Nearest to will: could, can, may, did, to, cannot, might, inspires,\n",
      "Nearest to seven: nine, eight, four, surgeries, bowie, shipments, percentile, caustic,\n",
      "Nearest to one: talib, cartier, circumstantial, bitterness, akc, zero, quantification, ripper,\n",
      "Nearest to UNK: gulf, dusseldorf, witten, rakis, plundering, armature, persecutions, bear,\n",
      "Nearest to on: island, erebus, ross, sweep, active, market, dolphin, donkey,\n",
      "Nearest to into: reviewer, opener, costume, horribilis, ursula, brings, cozy, buckland,\n",
      "Average loss at step 12000: 4.694953\n",
      "Average loss at step 14000: 4.582830\n",
      "Average loss at step 16000: 4.314434\n",
      "Average loss at step 18000: 4.392874\n",
      "Average loss at step 20000: 4.263382\n",
      "Nearest to over: upbringing, intrigued, bombs, cocoa, cravings, circumcised, kouchner, cigars,\n",
      "Nearest to known: chap, described, such, doing, judeo, juice, abominable, ghb,\n",
      "Nearest to may: would, should, can, to, must, might, could, cannot,\n",
      "Nearest to after: before, medals, sennett, pronouncing, ux, behind, francophone, lithuanian,\n",
      "Nearest to at: speller, schistosomiasis, equalizer, revolutionize, anubis, sto, sortavala, castle,\n",
      "Nearest to more: typically, iers, less, rather, eps, solute, aground, openstep,\n",
      "Nearest to only: past, innes, ascorbic, selectively, professions, invalid, unsettled, bacchus,\n",
      "Nearest to from: mikoyan, dishonesty, plectrum, in, on, outfielder, alfv, breve,\n",
      "Nearest to four: gave, six, seven, nine, three, two, landau, brigade,\n",
      "Nearest to b: d, popularizing, dermal, drawings, core, politician, teborg, woke,\n",
      "Nearest to will: could, would, should, testimonium, can, did, must, may,\n",
      "Nearest to seven: three, four, nine, stumbling, two, zero, six, five,\n",
      "Nearest to one: trivium, proton, mph, schneider, particle, humour, cantilever, envision,\n",
      "Nearest to UNK: ath, fethry, hani, olson, clipperton, malays, cosmonauts, hooked,\n",
      "Nearest to on: within, in, votive, latveria, ned, for, armory, bol,\n",
      "Nearest to into: to, coeducational, leche, eggs, generalizes, making, garden, unproductive,\n",
      "Average loss at step 22000: 4.123037\n",
      "Average loss at step 24000: 4.227012\n",
      "Average loss at step 26000: 3.958049\n",
      "Average loss at step 28000: 3.836250\n",
      "Average loss at step 30000: 3.799360\n",
      "Nearest to over: mclaughlin, hbar, rooney, nr, bronchitis, viterbo, vied, frontiersman,\n",
      "Nearest to known: referred, described, used, ferraris, regarded, mellor, famous, far,\n",
      "Nearest to may: can, should, must, would, could, might, will, to,\n",
      "Nearest to after: mississippian, daimyo, marjoram, for, before, sukhum, fairey, afterwards,\n",
      "Nearest to at: in, eridanus, emergent, roasting, thaddeus, mizrahi, for, during,\n",
      "Nearest to more: less, most, very, openstep, basins, ignores, pectoral, dose,\n",
      "Nearest to only: shaking, bishoprics, legalisation, aged, block, cavitation, castiglione, petra,\n",
      "Nearest to from: in, garibaldi, ale, ebbinghaus, towards, of, into, chancellors,\n",
      "Nearest to four: three, six, eight, zero, amorites, two, auk, five,\n",
      "Nearest to b: d, rockefeller, kar, tears, distinctions, popularize, vecchio, melancholy,\n",
      "Nearest to will: should, could, can, shall, may, must, would, constantin,\n",
      "Nearest to seven: five, eight, three, zero, nine, larch, tap, neutrinos,\n",
      "Nearest to one: riigikogu, millions, abeyance, saviola, schemas, ardal, protruding, zawahiri,\n",
      "Nearest to UNK: manley, lifeforms, leben, processes, loom, lossless, excess, landesverband,\n",
      "Nearest to on: in, bikes, during, hadn, bachelet, transcontinental, unintentional, from,\n",
      "Nearest to into: minced, hazael, from, legalisation, cylindrical, comanche, bucky, across,\n",
      "Average loss at step 32000: 3.813046\n",
      "Average loss at step 34000: 3.995079\n",
      "Average loss at step 36000: 3.865535\n",
      "Average loss at step 38000: 3.890003\n",
      "Average loss at step 40000: 3.851431\n",
      "Nearest to over: sacra, bosman, tether, mestre, manzarek, legume, from, glasnost,\n",
      "Nearest to known: recognized, described, referred, used, dyed, devour, abominable, identified,\n",
      "Nearest to may: will, might, must, can, should, would, could, cannot,\n",
      "Nearest to after: before, samarkand, so, of, medals, phylum, iib, aoc,\n",
      "Nearest to at: on, freedoms, under, when, in, platt, ratsiraka, defraud,\n",
      "Nearest to more: less, most, better, rather, greater, areal, allis, bodmin,\n",
      "Nearest to only: antibacterial, stabilizes, teal, yahweh, corps, universidad, wildstorm, thriving,\n",
      "Nearest to from: of, with, into, under, in, by, mikoyan, dekker,\n",
      "Nearest to four: two, lieberman, three, finalized, impeccable, gaiman, mizrahi, indomitable,\n",
      "Nearest to b: inflammatory, urn, upholds, criollo, islington, anasazi, aisle, birthright,\n",
      "Nearest to will: can, may, must, would, could, should, cannot, might,\n",
      "Nearest to seven: five, nine, yassin, edith, aediles, six, cursus, zero,\n",
      "Nearest to one: sacrament, cdots, vicious, garand, seven, booch, faroese, felons,\n",
      "Nearest to UNK: flogging, santiago, methylation, decolonization, roslin, tai, coaster, clowning,\n",
      "Nearest to on: at, in, into, since, aeolian, although, bock, through,\n",
      "Nearest to into: in, through, on, from, coniferous, holbein, rebates, inapplicable,\n",
      "Average loss at step 42000: 3.770257\n",
      "Average loss at step 44000: 3.793840\n",
      "Average loss at step 46000: 3.675022\n",
      "Average loss at step 48000: 3.820206\n",
      "Average loss at step 50000: 3.626803\n",
      "Nearest to over: against, before, after, at, under, improperly, spent, for,\n",
      "Nearest to known: referred, used, seen, regarded, viewed, understood, believed, released,\n",
      "Nearest to may: can, should, could, must, would, cannot, might, did,\n",
      "Nearest to after: at, in, medals, of, before, over, despite, for,\n",
      "Nearest to at: after, over, in, einer, ronstadt, speller, flowery, mikoyan,\n",
      "Nearest to more: less, rather, conscription, most, felons, lcds, openstep, breakdancing,\n",
      "Nearest to only: pwn, diaries, plekhanov, janet, fixtures, karnataka, kelvin, always,\n",
      "Nearest to from: dekker, upon, fundamento, toward, watcher, into, in, leste,\n",
      "Nearest to four: three, zero, seven, six, five, eight, gauguin, nine,\n",
      "Nearest to b: d, sgml, anasazi, scholarships, bot, bylaws, tir, taland,\n",
      "Nearest to will: would, could, must, can, might, should, may, cannot,\n",
      "Nearest to seven: six, eight, nine, four, five, hammurabi, calamities, anmen,\n",
      "Nearest to one: abeyance, readability, eight, kludge, reproducible, upanishads, dnia, goods,\n",
      "Nearest to UNK: ben, berenson, toulouse, serre, keynesians, missed, bassoons, encha,\n",
      "Nearest to on: upon, in, throughout, mallets, monica, cozy, interrogation, islami,\n",
      "Nearest to into: from, peanut, veneer, lamp, clouded, to, battista, kondratiev,\n",
      "Average loss at step 52000: 3.665195\n",
      "Average loss at step 54000: 3.803944\n",
      "Average loss at step 56000: 3.754416\n",
      "Average loss at step 58000: 3.597679\n",
      "Average loss at step 60000: 3.684957\n",
      "Nearest to over: during, at, through, throughout, camden, estado, unitarian, tuscan,\n",
      "Nearest to known: referred, regarded, used, described, identified, considered, served, depicted,\n",
      "Nearest to may: can, might, would, should, must, could, will, cannot,\n",
      "Nearest to after: before, wis, hoses, metis, buell, nearly, finals, impetuous,\n",
      "Nearest to at: in, over, alligators, pinocchio, for, vaikundar, riddler, brindisi,\n",
      "Nearest to more: less, rather, better, greater, how, most, stances, ferro,\n",
      "Nearest to only: who, bordeaux, always, austere, iona, aphids, i, polluted,\n",
      "Nearest to from: into, in, giving, on, mikoyan, patenting, through, with,\n",
      "Nearest to four: five, advocating, six, dada, falsified, hedgehog, toss, eight,\n",
      "Nearest to b: lysergic, isuzu, ab, uranhay, p, virtuous, alkoxide, singh,\n",
      "Nearest to will: could, can, may, must, would, might, should, vitry,\n",
      "Nearest to seven: nine, eight, harrier, five, x, vald, dogmas, everyman,\n",
      "Nearest to one: completions, cuon, dnia, connelly, superscalar, tyrannical, two, pedantic,\n",
      "Nearest to UNK: und, widowers, pollutants, angiosperms, hermitage, sacks, inwards, abalone,\n",
      "Nearest to on: above, from, upon, in, by, amherst, tubas, pryor,\n",
      "Nearest to into: from, in, drab, primigenius, by, like, vacations, fangio,\n",
      "Average loss at step 62000: 3.691642\n",
      "Average loss at step 64000: 3.723353\n",
      "Average loss at step 66000: 3.321085\n",
      "Average loss at step 68000: 3.303415\n",
      "Average loss at step 70000: 3.627278\n",
      "Nearest to over: on, throughout, of, through, advisory, ten, during, together,\n",
      "Nearest to known: regarded, served, referred, classified, recognized, described, considered, portrayed,\n",
      "Nearest to may: might, can, could, should, will, would, must, cannot,\n",
      "Nearest to after: pv, gbase, prelog, before, electrolyte, during, discharged, hibbert,\n",
      "Nearest to at: during, associates, sedan, in, slipper, scrupulously, on, stadler,\n",
      "Nearest to more: less, rather, greater, higher, most, very, larger, openstep,\n",
      "Nearest to only: bottlenose, laine, ample, deletions, joliot, resides, glaciations, calicut,\n",
      "Nearest to from: in, into, across, between, until, mikoyan, on, within,\n",
      "Nearest to four: three, five, six, eight, seven, zero, kashubian, pellets,\n",
      "Nearest to b: programmable, constellations, letterboxes, marathas, subhas, tumour, tarkovsky, manipulating,\n",
      "Nearest to will: would, can, must, could, may, might, should, cannot,\n",
      "Nearest to seven: three, eight, uttered, four, nine, six, five, zero,\n",
      "Nearest to one: unrequited, canned, accordance, everly, algeria, cochrane, christiern, wines,\n",
      "Nearest to UNK: befell, harlequin, cerrado, beep, tiled, www, gibbs, vagus,\n",
      "Nearest to on: upon, in, since, over, through, of, for, from,\n",
      "Nearest to into: from, cryonicists, by, when, ges, knit, quicksort, railhead,\n",
      "Average loss at step 72000: 3.471719\n",
      "Average loss at step 74000: 3.641736\n",
      "Average loss at step 76000: 3.430173\n",
      "Average loss at step 78000: 3.619408\n",
      "Average loss at step 80000: 3.473169\n",
      "Nearest to over: pew, baserunner, blaze, throughout, mainframe, beyond, during, lodger,\n",
      "Nearest to known: regarded, referred, served, classified, described, used, recognized, possible,\n",
      "Nearest to may: can, must, might, would, should, cannot, could, does,\n",
      "Nearest to after: before, during, for, actinidia, olivier, and, in, mackaye,\n",
      "Nearest to at: where, vauban, in, from, wands, testosterone, speller, during,\n",
      "Nearest to more: less, stronger, rather, greater, better, increasingly, quick, fewer,\n",
      "Nearest to only: practically, diaries, regimens, ziegfeld, hoffer, sedation, tapping, magnates,\n",
      "Nearest to from: and, into, with, in, on, across, including, baxter,\n",
      "Nearest to four: three, five, six, seven, eight, vantage, nine, celsius,\n",
      "Nearest to b: gen, zawahiri, sidebands, clarke, hasse, traits, figure, gilliam,\n",
      "Nearest to will: would, can, must, should, did, cannot, shall, might,\n",
      "Nearest to seven: zero, three, eight, nine, five, four, six, sixteen,\n",
      "Nearest to one: driftwood, signified, contrast, expos, romanticized, pvt, steyr, hydrochloric,\n",
      "Nearest to UNK: h, plum, edsac, cad, di, o, ez, hypotension,\n",
      "Nearest to on: upon, in, beyond, across, overloading, from, retrieved, savoury,\n",
      "Nearest to into: from, in, during, handedly, across, xt, baserunners, endoplasmic,\n",
      "Average loss at step 82000: 3.585143\n",
      "Average loss at step 84000: 3.442535\n",
      "Average loss at step 86000: 3.457834\n",
      "Average loss at step 88000: 3.394592\n",
      "Average loss at step 90000: 3.325552\n",
      "Nearest to over: cic, impulses, ferrara, under, on, jaime, connolly, capp,\n",
      "Nearest to known: regarded, referred, used, described, portrayed, defined, served, classified,\n",
      "Nearest to may: would, can, could, might, must, cannot, will, should,\n",
      "Nearest to after: during, following, if, before, deir, on, of, and,\n",
      "Nearest to at: of, during, maui, precipitating, around, reached, lest, with,\n",
      "Nearest to more: less, rather, most, stronger, better, quick, fewer, felons,\n",
      "Nearest to only: angular, cuny, unsuitable, aircraft, wp, minimal, chueca, awry,\n",
      "Nearest to from: into, in, on, against, and, towards, through, leste,\n",
      "Nearest to four: three, five, eight, seven, lovers, zero, nuanced, lingo,\n",
      "Nearest to b: carbine, diego, di, barbarossa, gosling, k, barbaric, grandchildren,\n",
      "Nearest to will: could, would, should, might, can, must, may, cannot,\n",
      "Nearest to seven: six, eight, nine, four, three, luxembourgish, eq, aediles,\n",
      "Nearest to one: heijenoort, jotham, quadrilateral, alphabets, whitby, francis, thirties, gamma,\n",
      "Nearest to UNK: smith, nigerian, nelson, richardson, crouching, tom, impresario, anz,\n",
      "Nearest to on: upon, into, from, in, through, latveria, minster, across,\n",
      "Nearest to into: from, on, towards, in, across, ergative, skylark, beyond,\n",
      "Average loss at step 92000: 3.480624\n",
      "Average loss at step 94000: 3.488695\n",
      "Average loss at step 96000: 3.394813\n",
      "Average loss at step 98000: 3.491190\n",
      "Average loss at step 100000: 3.447110\n",
      "Nearest to over: renounced, ciboney, marquesas, motivate, off, during, abruptly, petrovich,\n",
      "Nearest to known: referred, described, regarded, used, defined, seen, called, identified,\n",
      "Nearest to may: can, might, should, would, could, must, will, cannot,\n",
      "Nearest to after: before, at, during, for, iib, afterwards, following, until,\n",
      "Nearest to at: after, in, speller, during, on, before, by, until,\n",
      "Nearest to more: less, faster, better, larger, rather, smaller, very, fewer,\n",
      "Nearest to only: adrift, heterochromatin, maududi, extraordinarily, four, officially, amu, coli,\n",
      "Nearest to from: into, in, through, of, and, back, until, reinventing,\n",
      "Nearest to four: five, six, two, three, zero, pellets, seven, zahn,\n",
      "Nearest to b: inverting, necropolis, uranium, barbarossa, waid, clock, healer, oldfield,\n",
      "Nearest to will: would, can, could, must, should, did, might, cannot,\n",
      "Nearest to seven: eight, nine, five, zero, six, four, th, bedfordshire,\n",
      "Nearest to one: foresight, subtitle, clamp, cth, seasons, stormed, somerset, foodcrops,\n",
      "Nearest to UNK: el, wilhelm, haggard, neocortex, retrieved, puget, crustaceans, hillel,\n",
      "Nearest to on: upon, minster, in, at, retrieved, concerning, vox, until,\n",
      "Nearest to into: from, through, inside, in, until, cryonicists, within, pwnage,\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, num_cbows, cbow_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": 68,
   "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": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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g2rdvz/79+wFYtmwZ7du3p02bNnTt2tWRqOTkyZMMGjSIoKAgQkJC+OyzzwBY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c0NfD5f6fksHQtv70lwcxsKiUQCQ0ND1lhjaRcoyuDz0RJS/K2V/fvD4ec3Dxoa0nu0c+e2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\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dhsaIcbDIk5qaSnw+n8rLy+nZs2fE5XIpPT2dESh5XSorK6mmpoaIiC5cuEBCoZA5pkh9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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x108368828>"
      ]
     },
     "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 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": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}