word2vec_implementation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Read 2087 labeled train reviews\n"
     ]
    }
   ],
   "source": [
    "# use python2\n",
    "'''\n",
    "0429\n",
    "Error analysis:\n",
    "dictionary too few words\n",
    "use word2vec to enrich our word list\n",
    "\n",
    "using all round7 reviews as corpus\n",
    "'''\n",
    "import pandas as pd\n",
    "\n",
    "# read\n",
    "train = pd.read_table(\"/Users/luxiaopeng/notebook/inls613/closure_prediction/review_by_business.txt\")\n",
    "# test = pd.read_csv( \"testData.tsv\", header=0, delimiter=\"\\t\", quoting=3 )\n",
    "# unlabeled_train = pd.read_csv( \"unlabeledTrainData.tsv\", header=0, \n",
    "#  delimiter=\"\\t\", quoting=3 )\n",
    "\n",
    "# Verify the number of reviews that were read (100,000 in total)\n",
    "print(\"Read %d labeled train reviews\" % (train[\"text\"].size))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "train.rename(columns={\"text\":\"review\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = train[[\"business_id\",\"review\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop na\n",
    "train = train.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import various modules for string cleaning\n",
    "from bs4 import BeautifulSoup\n",
    "import re\n",
    "from nltk.corpus import stopwords\n",
    "\n",
    "def review_to_wordlist(review, remove_stopwords = False):\n",
    "    # Function to convert a document to a sequence of words,\n",
    "    # optionally removing stop words.  Returns a list of words.\n",
    "    #\n",
    "    # 1. Remove HTML\n",
    "    review_text = BeautifulSoup(review).get_text()\n",
    "    #  \n",
    "    # 2. Remove non-letters\n",
    "    review_text = re.sub(\"[^a-zA-Z]\",\" \", review_text)\n",
    "    #\n",
    "    # 3. Convert words to lower case and split them\n",
    "    words = review_text.lower().split()\n",
    "    #\n",
    "    # 4. Optionally remove stop words (false by default)\n",
    "    if remove_stopwords:\n",
    "        stops = set(stopwords.words(\"english\"))\n",
    "        words = [w for w in words if not w in stops]\n",
    "    #\n",
    "    # 5. Return a list of words\n",
    "    return(words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Next, we want a specific input format. Word2Vec expects single sentences, \n",
    "each one as a list of words. In other words, the input format is a list of lists.\n",
    "\n",
    "It is not at all straightforward how to split a paragraph into sentences. \n",
    "There are all kinds of gotchas in natural language. English sentences can \n",
    "end with \"?\", \"!\", \"\"\", or \".\", among other things, and spacing and \n",
    "capitalization are not reliable guides either. For this reason, \n",
    "we'll use NLTK's punkt tokenizer for sentence splitting. In order to \n",
    "use this, you will need to install NLTK and use nltk.download() to \n",
    "download the relevant training file for punkt.\n",
    "'''\n",
    "# Download the punkt tokenizer for sentence splitting\n",
    "import nltk.data\n",
    "# nltk.download('popular')\n",
    "# Load the punkt tokenizer\n",
    "tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')\n",
    "\n",
    "# Define a function to split a review into parsed sentences\n",
    "def review_to_sentences(review, tokenizer, remove_stopwords = False):\n",
    "    # Function to split a review into parsed sentences. Returns a \n",
    "    # list of sentences, where each sentence is a list of words\n",
    "    #\n",
    "    # 1. Use the NLTK tokenizer to split the paragraph into sentences\n",
    "    raw_sentences = tokenizer.tokenize(review.decode('utf-8').strip())\n",
    "    #\n",
    "    # 2. Loop over each sentence\n",
    "    sentences = []\n",
    "    for raw_sentence in raw_sentences:\n",
    "        # If a sentence is empty, skip it\n",
    "        if len(raw_sentence) > 0:\n",
    "            # Otherwise, call review_to_wordlist to get a list of words\n",
    "            sentences.append(review_to_wordlist(raw_sentence, remove_stopwords))\n",
    "    #\n",
    "    # Return the list of sentences (each sentence is a list of words,\n",
    "    # so this returns a list of lists\n",
    "    return sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentences = []\n",
    "print('parsing sentences from training set')\n",
    "for review in train['review']:\n",
    "    sentences += review_to_sentences(review, tokenizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'sentences' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-d2f019d9f556>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# check\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mprint\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msentences\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'sentences' is not defined"
     ]
    }
   ],
   "source": [
    "# check\n",
    "print len(sentences)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "\n",
    "with open('sentence_5m.pkl', 'rb') as f:\n",
    "    sentences = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:31:26,407 : INFO : 'pattern' package not found; tag filters are not available for English\n",
      "2018-04-30 19:31:26,429 : INFO : collecting all words and their counts\n",
      "2018-04-30 19:31:26,432 : INFO : PROGRESS: at sentence #0, processed 0 words, keeping 0 word types\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training model...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:33:06,575 : INFO : PROGRESS: at sentence #730000, processed 10371563 words, keeping 67003 word types\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:35:05,940 : INFO : PROGRESS: at sentence #1440000, processed 20407767 words, keeping 90909 word types\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:38:19,942 : INFO : PROGRESS: at sentence #2150000, processed 30433349 words, keeping 110895 word types\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:41:49,704 : INFO : PROGRESS: at sentence #2860000, processed 40511648 words, keeping 128163 word types\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:46:15,246 : INFO : PROGRESS: at sentence #3570000, processed 50579592 words, keeping 143982 word types\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:49:27,333 : INFO : PROGRESS: at sentence #4280000, processed 60632552 words, keeping 160132 word types\n",
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      "2018-04-30 19:51:11,326 : INFO : PROGRESS: at sentence #4780000, processed 67738101 words, keeping 169441 word types\n",
      "2018-04-30 19:51:12,797 : INFO : PROGRESS: at sentence #4790000, processed 67883949 words, keeping 169651 word types\n",
      "2018-04-30 19:51:15,124 : INFO : PROGRESS: at sentence #4800000, processed 68033086 words, keeping 169871 word types\n",
      "2018-04-30 19:51:17,101 : INFO : PROGRESS: at sentence #4810000, processed 68178647 words, keeping 170121 word types\n",
      "2018-04-30 19:51:19,221 : INFO : PROGRESS: at sentence #4820000, processed 68327010 words, keeping 170372 word types\n",
      "2018-04-30 19:51:21,462 : INFO : PROGRESS: at sentence #4830000, processed 68470421 words, keeping 170560 word types\n",
      "2018-04-30 19:51:23,318 : INFO : PROGRESS: at sentence #4840000, processed 68604930 words, keeping 170755 word types\n",
      "2018-04-30 19:51:25,688 : INFO : PROGRESS: at sentence #4850000, processed 68756148 words, keeping 170950 word types\n",
      "2018-04-30 19:51:27,727 : INFO : PROGRESS: at sentence #4860000, processed 68904949 words, keeping 171174 word types\n",
      "2018-04-30 19:51:30,454 : INFO : PROGRESS: at sentence #4870000, processed 69055666 words, keeping 171404 word types\n",
      "2018-04-30 19:51:32,443 : INFO : PROGRESS: at sentence #4880000, processed 69205106 words, keeping 171603 word types\n",
      "2018-04-30 19:51:35,010 : INFO : PROGRESS: at sentence #4890000, processed 69358943 words, keeping 171753 word types\n",
      "2018-04-30 19:51:36,675 : INFO : PROGRESS: at sentence #4900000, processed 69503775 words, keeping 171969 word types\n",
      "2018-04-30 19:51:39,532 : INFO : PROGRESS: at sentence #4910000, processed 69654345 words, keeping 172176 word types\n",
      "2018-04-30 19:51:41,229 : INFO : PROGRESS: at sentence #4920000, processed 69792678 words, keeping 172352 word types\n",
      "2018-04-30 19:51:43,964 : INFO : PROGRESS: at sentence #4930000, processed 69931157 words, keeping 172545 word types\n",
      "2018-04-30 19:51:45,294 : INFO : PROGRESS: at sentence #4940000, processed 70061877 words, keeping 172701 word types\n",
      "2018-04-30 19:51:47,846 : INFO : PROGRESS: at sentence #4950000, processed 70190224 words, keeping 172860 word types\n",
      "2018-04-30 19:51:49,641 : INFO : PROGRESS: at sentence #4960000, processed 70325574 words, keeping 173046 word types\n",
      "2018-04-30 19:51:52,407 : INFO : PROGRESS: at sentence #4970000, processed 70465662 words, keeping 173210 word types\n",
      "2018-04-30 19:51:53,735 : INFO : PROGRESS: at sentence #4980000, processed 70598396 words, keeping 173363 word types\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:51:55,608 : INFO : PROGRESS: at sentence #4990000, processed 70751109 words, keeping 173495 word types\n",
      "2018-04-30 19:51:58,054 : INFO : collected 173638 word types from a corpus of 70896303 raw words and 5000000 sentences\n",
      "2018-04-30 19:51:58,063 : INFO : Loading a fresh vocabulary\n",
      "2018-04-30 19:52:38,577 : INFO : min_count=5 retains 54796 unique words (31% of original 173638, drops 118842)\n",
      "2018-04-30 19:52:38,599 : INFO : min_count=5 leaves 70717024 word corpus (99% of original 70896303, drops 179279)\n",
      "2018-04-30 19:52:39,338 : INFO : deleting the raw counts dictionary of 173638 items\n",
      "2018-04-30 19:52:39,374 : INFO : sample=0.001 downsamples 56 most-common words\n",
      "2018-04-30 19:52:39,378 : INFO : downsampling leaves estimated 52231415 word corpus (73.9% of prior 70717024)\n",
      "2018-04-30 19:52:39,786 : INFO : estimated required memory for 54796 words and 300 dimensions: 158908400 bytes\n",
      "2018-04-30 19:52:39,788 : INFO : resetting layer weights\n",
      "2018-04-30 19:52:43,839 : INFO : training model with 4 workers on 54796 vocabulary and 300 features, using sg=0 hs=0 sample=0.001 negative=5 window=10\n",
      "2018-04-30 19:52:44,963 : INFO : EPOCH 1 - PROGRESS: at 0.24% examples, 121426 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:52:46,010 : INFO : EPOCH 1 - PROGRESS: at 0.73% examples, 190100 words/s, in_qsize 5, out_qsize 2\n",
      "2018-04-30 19:52:46,996 : INFO : EPOCH 1 - PROGRESS: at 1.24% examples, 213736 words/s, in_qsize 3, out_qsize 0\n",
      "2018-04-30 19:52:48,016 : INFO : EPOCH 1 - PROGRESS: at 1.75% examples, 226924 words/s, in_qsize 3, out_qsize 0\n",
      "2018-04-30 19:52:49,028 : INFO : EPOCH 1 - PROGRESS: at 2.14% examples, 222109 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:52:50,047 : INFO : EPOCH 1 - PROGRESS: at 2.51% examples, 216710 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:52:51,113 : INFO : EPOCH 1 - PROGRESS: at 2.85% examples, 211761 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:52:52,098 : INFO : EPOCH 1 - PROGRESS: at 3.18% examples, 206160 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:52:53,141 : INFO : EPOCH 1 - PROGRESS: at 3.60% examples, 206745 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:52:54,151 : INFO : EPOCH 1 - PROGRESS: at 4.02% examples, 207113 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:52:55,174 : INFO : EPOCH 1 - PROGRESS: at 4.33% examples, 203307 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:52:56,193 : INFO : EPOCH 1 - PROGRESS: at 4.74% examples, 203844 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:52:57,194 : INFO : EPOCH 1 - PROGRESS: at 5.22% examples, 207838 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:52:58,229 : INFO : EPOCH 1 - PROGRESS: at 5.63% examples, 207196 words/s, in_qsize 6, out_qsize 1\n",
      "2018-04-30 19:52:59,331 : INFO : EPOCH 1 - PROGRESS: at 5.86% examples, 200788 words/s, in_qsize 6, out_qsize 1\n",
      "2018-04-30 19:53:00,316 : INFO : EPOCH 1 - PROGRESS: at 6.25% examples, 200090 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:01,317 : INFO : EPOCH 1 - PROGRESS: at 6.72% examples, 202576 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:02,387 : INFO : EPOCH 1 - PROGRESS: at 7.30% examples, 208244 words/s, in_qsize 5, out_qsize 2\n",
      "2018-04-30 19:53:03,346 : INFO : EPOCH 1 - PROGRESS: at 7.77% examples, 209945 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:53:04,368 : INFO : EPOCH 1 - PROGRESS: at 8.31% examples, 213002 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:05,372 : INFO : EPOCH 1 - PROGRESS: at 8.79% examples, 214674 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:06,428 : INFO : EPOCH 1 - PROGRESS: at 9.29% examples, 216012 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:53:07,476 : INFO : EPOCH 1 - PROGRESS: at 9.84% examples, 218608 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:53:08,596 : INFO : EPOCH 1 - PROGRESS: at 10.14% examples, 215237 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:09,689 : INFO : EPOCH 1 - PROGRESS: at 10.43% examples, 211811 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:10,693 : INFO : EPOCH 1 - PROGRESS: at 10.93% examples, 213760 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:11,748 : INFO : EPOCH 1 - PROGRESS: at 11.46% examples, 215416 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:53:12,767 : INFO : EPOCH 1 - PROGRESS: at 11.94% examples, 216457 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:53:13,775 : INFO : EPOCH 1 - PROGRESS: at 12.48% examples, 218503 words/s, in_qsize 5, out_qsize 1\n",
      "2018-04-30 19:53:14,854 : INFO : EPOCH 1 - PROGRESS: at 12.93% examples, 218482 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:15,855 : INFO : EPOCH 1 - PROGRESS: at 13.40% examples, 219449 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:16,909 : INFO : EPOCH 1 - PROGRESS: at 13.98% examples, 221771 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:53:17,958 : INFO : EPOCH 1 - PROGRESS: at 14.34% examples, 220362 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:53:19,041 : INFO : EPOCH 1 - PROGRESS: at 14.56% examples, 216690 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:53:20,064 : INFO : EPOCH 1 - PROGRESS: at 14.86% examples, 215042 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:21,078 : INFO : EPOCH 1 - PROGRESS: at 15.32% examples, 215516 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:22,097 : INFO : EPOCH 1 - PROGRESS: at 15.77% examples, 216153 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:23,160 : INFO : EPOCH 1 - PROGRESS: at 16.38% examples, 218392 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:24,275 : INFO : EPOCH 1 - PROGRESS: at 16.88% examples, 219494 words/s, in_qsize 6, out_qsize 2\n",
      "2018-04-30 19:53:25,201 : INFO : EPOCH 1 - PROGRESS: at 17.21% examples, 218461 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:26,176 : INFO : EPOCH 1 - PROGRESS: at 17.51% examples, 217106 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:27,258 : INFO : EPOCH 1 - PROGRESS: at 17.96% examples, 216943 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:28,354 : INFO : EPOCH 1 - PROGRESS: at 18.30% examples, 215555 words/s, in_qsize 3, out_qsize 0\n",
      "2018-04-30 19:53:29,361 : INFO : EPOCH 1 - PROGRESS: at 18.61% examples, 214331 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:30,389 : INFO : EPOCH 1 - PROGRESS: at 18.92% examples, 213078 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:31,398 : INFO : EPOCH 1 - PROGRESS: at 19.29% examples, 212574 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:53:32,416 : INFO : EPOCH 1 - PROGRESS: at 19.68% examples, 212365 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:33,436 : INFO : EPOCH 1 - PROGRESS: at 20.25% examples, 213791 words/s, in_qsize 2, out_qsize 1\n",
      "2018-04-30 19:53:34,438 : INFO : EPOCH 1 - PROGRESS: at 20.74% examples, 214666 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:53:35,470 : INFO : EPOCH 1 - PROGRESS: at 21.23% examples, 215218 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:36,552 : INFO : EPOCH 1 - PROGRESS: at 21.75% examples, 215835 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:53:37,570 : INFO : EPOCH 1 - PROGRESS: at 22.13% examples, 215467 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:53:38,617 : INFO : EPOCH 1 - PROGRESS: at 22.40% examples, 214028 words/s, in_qsize 8, out_qsize 4\n",
      "2018-04-30 19:53:39,589 : INFO : EPOCH 1 - PROGRESS: at 22.65% examples, 212535 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:40,621 : INFO : EPOCH 1 - PROGRESS: at 22.95% examples, 211400 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:41,666 : INFO : EPOCH 1 - PROGRESS: at 23.35% examples, 211168 words/s, in_qsize 2, out_qsize 0\n",
      "2018-04-30 19:53:42,668 : INFO : EPOCH 1 - PROGRESS: at 23.77% examples, 211167 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:43,729 : INFO : EPOCH 1 - PROGRESS: at 24.21% examples, 211113 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:44,998 : INFO : EPOCH 1 - PROGRESS: at 24.53% examples, 209629 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:53:45,943 : INFO : EPOCH 1 - PROGRESS: at 24.83% examples, 208845 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:53:46,936 : INFO : EPOCH 1 - PROGRESS: at 25.21% examples, 208683 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:47,994 : INFO : EPOCH 1 - PROGRESS: at 25.61% examples, 208620 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:53:48,944 : INFO : EPOCH 1 - PROGRESS: at 25.91% examples, 207801 words/s, in_qsize 4, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:53:50,040 : INFO : EPOCH 1 - PROGRESS: at 26.10% examples, 205812 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:51,120 : INFO : EPOCH 1 - PROGRESS: at 26.46% examples, 205548 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:53:52,087 : INFO : EPOCH 1 - PROGRESS: at 26.82% examples, 205251 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:53:53,141 : INFO : EPOCH 1 - PROGRESS: at 27.27% examples, 205732 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:53:54,208 : INFO : EPOCH 1 - PROGRESS: at 27.59% examples, 204832 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:55,236 : INFO : EPOCH 1 - PROGRESS: at 27.84% examples, 203740 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:56,280 : INFO : EPOCH 1 - PROGRESS: at 28.26% examples, 203858 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:57,389 : INFO : EPOCH 1 - PROGRESS: at 28.63% examples, 203680 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:53:58,292 : INFO : EPOCH 1 - PROGRESS: at 28.94% examples, 203185 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:53:59,364 : INFO : EPOCH 1 - PROGRESS: at 29.24% examples, 202448 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:00,487 : INFO : EPOCH 1 - PROGRESS: at 29.32% examples, 200353 words/s, in_qsize 7, out_qsize 2\n",
      "2018-04-30 19:54:01,390 : INFO : EPOCH 1 - PROGRESS: at 29.60% examples, 199632 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:54:02,450 : INFO : EPOCH 1 - PROGRESS: at 29.81% examples, 198251 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:03,503 : INFO : EPOCH 1 - PROGRESS: at 30.14% examples, 197949 words/s, in_qsize 6, out_qsize 2\n",
      "2018-04-30 19:54:04,501 : INFO : EPOCH 1 - PROGRESS: at 30.41% examples, 197139 words/s, in_qsize 8, out_qsize 1\n",
      "2018-04-30 19:54:05,573 : INFO : EPOCH 1 - PROGRESS: at 30.69% examples, 196266 words/s, in_qsize 6, out_qsize 1\n",
      "2018-04-30 19:54:06,633 : INFO : EPOCH 1 - PROGRESS: at 31.01% examples, 195712 words/s, in_qsize 8, out_qsize 1\n",
      "2018-04-30 19:54:07,771 : INFO : EPOCH 1 - PROGRESS: at 31.21% examples, 194286 words/s, in_qsize 7, out_qsize 3\n",
      "2018-04-30 19:54:08,842 : INFO : EPOCH 1 - PROGRESS: at 31.41% examples, 193047 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:09,930 : INFO : EPOCH 1 - PROGRESS: at 31.67% examples, 192153 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:10,942 : INFO : EPOCH 1 - PROGRESS: at 31.97% examples, 191607 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:11,954 : INFO : EPOCH 1 - PROGRESS: at 32.36% examples, 191661 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:12,979 : INFO : EPOCH 1 - PROGRESS: at 32.78% examples, 191945 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:54:13,981 : INFO : EPOCH 1 - PROGRESS: at 33.20% examples, 192265 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:15,044 : INFO : EPOCH 1 - PROGRESS: at 33.59% examples, 192287 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:16,114 : INFO : EPOCH 1 - PROGRESS: at 34.01% examples, 192509 words/s, in_qsize 4, out_qsize 1\n",
      "2018-04-30 19:54:17,296 : INFO : EPOCH 1 - PROGRESS: at 34.20% examples, 191184 words/s, in_qsize 3, out_qsize 0\n",
      "2018-04-30 19:54:18,292 : INFO : EPOCH 1 - PROGRESS: at 34.40% examples, 190119 words/s, in_qsize 5, out_qsize 0\n",
      "2018-04-30 19:54:19,322 : INFO : EPOCH 1 - PROGRESS: at 34.76% examples, 190003 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:20,387 : INFO : EPOCH 1 - PROGRESS: at 35.05% examples, 189434 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:21,447 : INFO : EPOCH 1 - PROGRESS: at 35.36% examples, 189041 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:22,529 : INFO : EPOCH 1 - PROGRESS: at 35.77% examples, 189213 words/s, in_qsize 5, out_qsize 1\n",
      "2018-04-30 19:54:23,478 : INFO : EPOCH 1 - PROGRESS: at 36.12% examples, 189089 words/s, in_qsize 7, out_qsize 2\n",
      "2018-04-30 19:54:24,502 : INFO : EPOCH 1 - PROGRESS: at 36.47% examples, 188949 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:25,575 : INFO : EPOCH 1 - PROGRESS: at 36.81% examples, 188788 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:54:26,560 : INFO : EPOCH 1 - PROGRESS: at 37.04% examples, 188039 words/s, in_qsize 4, out_qsize 0\n",
      "2018-04-30 19:54:27,589 : INFO : EPOCH 1 - PROGRESS: at 37.23% examples, 187091 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:28,602 : INFO : EPOCH 1 - PROGRESS: at 37.62% examples, 187193 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:54:29,643 : INFO : EPOCH 1 - PROGRESS: at 37.97% examples, 187030 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:30,690 : INFO : EPOCH 1 - PROGRESS: at 38.23% examples, 186443 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:31,805 : INFO : EPOCH 1 - PROGRESS: at 38.63% examples, 186504 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:32,901 : INFO : EPOCH 1 - PROGRESS: at 38.90% examples, 185925 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 19:54:33,943 : INFO : EPOCH 1 - PROGRESS: at 39.08% examples, 185050 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:34,995 : INFO : EPOCH 1 - PROGRESS: at 39.18% examples, 183739 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:36,075 : INFO : EPOCH 1 - PROGRESS: at 39.45% examples, 183288 words/s, in_qsize 8, out_qsize 1\n",
      "2018-04-30 19:54:37,108 : INFO : EPOCH 1 - PROGRESS: at 39.81% examples, 183419 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:54:38,111 : INFO : EPOCH 1 - PROGRESS: at 40.13% examples, 183255 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:54:39,144 : INFO : EPOCH 1 - PROGRESS: at 40.39% examples, 182767 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:40,214 : INFO : EPOCH 1 - PROGRESS: at 40.57% examples, 181981 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:41,262 : INFO : EPOCH 1 - PROGRESS: at 40.71% examples, 180919 words/s, in_qsize 5, out_qsize 1\n",
      "2018-04-30 19:54:42,292 : INFO : EPOCH 1 - PROGRESS: at 40.89% examples, 180154 words/s, in_qsize 5, out_qsize 1\n",
      "2018-04-30 19:54:43,340 : INFO : EPOCH 1 - PROGRESS: at 41.21% examples, 179988 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:44,360 : INFO : EPOCH 1 - PROGRESS: at 41.58% examples, 180087 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:45,370 : INFO : EPOCH 1 - PROGRESS: at 41.93% examples, 180074 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:46,389 : INFO : EPOCH 1 - PROGRESS: at 42.35% examples, 180389 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:47,458 : INFO : EPOCH 1 - PROGRESS: at 42.84% examples, 180978 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:54:48,541 : INFO : EPOCH 1 - PROGRESS: at 43.00% examples, 180054 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:54:49,556 : INFO : EPOCH 1 - PROGRESS: at 43.12% examples, 179129 words/s, in_qsize 6, out_qsize 0\n",
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      "2018-04-30 19:55:05,090 : INFO : EPOCH 1 - PROGRESS: at 48.29% examples, 178592 words/s, in_qsize 7, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:55:06,125 : INFO : EPOCH 1 - PROGRESS: at 48.68% examples, 178779 words/s, in_qsize 7, out_qsize 2\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:56:22,175 : INFO : EPOCH 1 - PROGRESS: at 77.05% examples, 184491 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 19:57:03,992 : INFO : worker thread finished; awaiting finish of 3 more threads\n",
      "2018-04-30 19:57:04,005 : INFO : worker thread finished; awaiting finish of 2 more threads\n",
      "2018-04-30 19:57:04,024 : INFO : worker thread finished; awaiting finish of 1 more threads\n",
      "2018-04-30 19:57:04,033 : INFO : worker thread finished; awaiting finish of 0 more threads\n",
      "2018-04-30 19:57:04,037 : INFO : EPOCH - 1 : training on 70896303 raw words (52228922 effective words) took 260.1s, 200798 effective words/s\n",
      "2018-04-30 19:57:05,074 : INFO : EPOCH 2 - PROGRESS: at 0.76% examples, 398676 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 19:57:31,688 : INFO : EPOCH 2 - PROGRESS: at 18.43% examples, 349020 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:57:32,807 : INFO : EPOCH 2 - PROGRESS: at 18.81% examples, 342369 words/s, in_qsize 7, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:57:33,815 : INFO : EPOCH 2 - PROGRESS: at 19.27% examples, 338682 words/s, in_qsize 7, out_qsize 0\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 19:58:49,420 : INFO : EPOCH 2 - PROGRESS: at 64.54% examples, 319802 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 19:59:42,324 : INFO : EPOCH 2 - PROGRESS: at 91.50% examples, 301737 words/s, in_qsize 8, out_qsize 1\n",
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      "2018-04-30 19:59:44,318 : INFO : EPOCH 2 - PROGRESS: at 93.07% examples, 302947 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:45,354 : INFO : EPOCH 2 - PROGRESS: at 93.80% examples, 303451 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:46,358 : INFO : EPOCH 2 - PROGRESS: at 94.51% examples, 303966 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:47,378 : INFO : EPOCH 2 - PROGRESS: at 95.28% examples, 304578 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:48,405 : INFO : EPOCH 2 - PROGRESS: at 96.03% examples, 305153 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 19:59:49,395 : INFO : EPOCH 2 - PROGRESS: at 96.71% examples, 305466 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:50,423 : INFO : EPOCH 2 - PROGRESS: at 97.47% examples, 306092 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:51,442 : INFO : EPOCH 2 - PROGRESS: at 98.15% examples, 306460 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:59:52,451 : INFO : EPOCH 2 - PROGRESS: at 98.95% examples, 306968 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:53,460 : INFO : EPOCH 2 - PROGRESS: at 99.76% examples, 307551 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:53,758 : INFO : worker thread finished; awaiting finish of 3 more threads\n",
      "2018-04-30 19:59:53,775 : INFO : worker thread finished; awaiting finish of 2 more threads\n",
      "2018-04-30 19:59:53,779 : INFO : worker thread finished; awaiting finish of 1 more threads\n",
      "2018-04-30 19:59:53,792 : INFO : worker thread finished; awaiting finish of 0 more threads\n",
      "2018-04-30 19:59:53,794 : INFO : EPOCH - 2 : training on 70896303 raw words (52229896 effective words) took 169.7s, 307711 effective words/s\n",
      "2018-04-30 19:59:54,821 : INFO : EPOCH 3 - PROGRESS: at 0.71% examples, 379710 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:59:55,840 : INFO : EPOCH 3 - PROGRESS: at 1.59% examples, 413577 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:56,844 : INFO : EPOCH 3 - PROGRESS: at 2.39% examples, 414648 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:59:57,845 : INFO : EPOCH 3 - PROGRESS: at 3.15% examples, 413948 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 19:59:58,847 : INFO : EPOCH 3 - PROGRESS: at 3.97% examples, 414625 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 19:59:59,890 : INFO : EPOCH 3 - PROGRESS: at 4.78% examples, 414930 words/s, in_qsize 8, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:00:00,895 : INFO : EPOCH 3 - PROGRESS: at 5.62% examples, 417189 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:01,914 : INFO : EPOCH 3 - PROGRESS: at 6.42% examples, 416329 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 20:00:02,961 : INFO : EPOCH 3 - PROGRESS: at 7.26% examples, 416464 words/s, in_qsize 5, out_qsize 1\n",
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      "2018-04-30 20:00:05,012 : INFO : EPOCH 3 - PROGRESS: at 8.75% examples, 409699 words/s, in_qsize 7, out_qsize 1\n",
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      "2018-04-30 20:00:07,077 : INFO : EPOCH 3 - PROGRESS: at 10.38% examples, 409107 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:08,111 : INFO : EPOCH 3 - PROGRESS: at 10.65% examples, 389772 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:09,142 : INFO : EPOCH 3 - PROGRESS: at 10.82% examples, 369316 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:10,168 : INFO : EPOCH 3 - PROGRESS: at 11.09% examples, 354678 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:11,176 : INFO : EPOCH 3 - PROGRESS: at 11.22% examples, 337899 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:00:16,284 : INFO : EPOCH 3 - PROGRESS: at 12.48% examples, 290183 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:17,316 : INFO : EPOCH 3 - PROGRESS: at 13.04% examples, 289966 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:18,346 : INFO : EPOCH 3 - PROGRESS: at 13.66% examples, 291259 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:19,372 : INFO : EPOCH 3 - PROGRESS: at 14.26% examples, 291649 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:20,394 : INFO : EPOCH 3 - PROGRESS: at 14.92% examples, 293491 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:22,480 : INFO : EPOCH 3 - PROGRESS: at 15.63% examples, 285223 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:23,552 : INFO : EPOCH 3 - PROGRESS: at 15.73% examples, 276672 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:24,638 : INFO : EPOCH 3 - PROGRESS: at 16.06% examples, 272585 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:25,623 : INFO : EPOCH 3 - PROGRESS: at 16.60% examples, 272825 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:26,674 : INFO : EPOCH 3 - PROGRESS: at 17.01% examples, 270857 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:00:29,716 : INFO : EPOCH 3 - PROGRESS: at 18.31% examples, 266953 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:00:30,736 : INFO : EPOCH 3 - PROGRESS: at 18.85% examples, 267145 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 20:00:31,886 : INFO : EPOCH 3 - PROGRESS: at 19.25% examples, 264485 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:32,918 : INFO : EPOCH 3 - PROGRESS: at 19.47% examples, 260525 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:33,948 : INFO : EPOCH 3 - PROGRESS: at 19.83% examples, 258436 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:34,948 : INFO : EPOCH 3 - PROGRESS: at 20.38% examples, 259132 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:00:36,996 : INFO : EPOCH 3 - PROGRESS: at 21.27% examples, 257419 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:00:39,058 : INFO : EPOCH 3 - PROGRESS: at 21.97% examples, 253511 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:40,066 : INFO : EPOCH 3 - PROGRESS: at 22.31% examples, 251816 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:41,153 : INFO : EPOCH 3 - PROGRESS: at 22.82% examples, 251884 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 20:00:42,201 : INFO : EPOCH 3 - PROGRESS: at 23.19% examples, 250287 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:43,266 : INFO : EPOCH 3 - PROGRESS: at 23.65% examples, 249660 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:00:44,279 : INFO : EPOCH 3 - PROGRESS: at 24.20% examples, 250043 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:00:46,328 : INFO : EPOCH 3 - PROGRESS: at 25.13% examples, 249551 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:00:49,516 : INFO : EPOCH 3 - PROGRESS: at 26.61% examples, 249160 words/s, in_qsize 8, out_qsize 1\n",
      "2018-04-30 20:00:50,527 : INFO : EPOCH 3 - PROGRESS: at 27.02% examples, 248626 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:00:53,583 : INFO : EPOCH 3 - PROGRESS: at 28.45% examples, 248518 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:00:59,725 : INFO : EPOCH 3 - PROGRESS: at 31.97% examples, 252974 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:01:00,735 : INFO : EPOCH 3 - PROGRESS: at 32.52% examples, 253454 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:01:01,751 : INFO : EPOCH 3 - PROGRESS: at 32.86% examples, 252273 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:01:02,785 : INFO : EPOCH 3 - PROGRESS: at 33.06% examples, 249987 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:01:06,249 : INFO : EPOCH 3 - PROGRESS: at 34.03% examples, 245048 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:01:09,268 : INFO : EPOCH 3 - PROGRESS: at 35.50% examples, 245327 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:01:11,325 : INFO : EPOCH 3 - PROGRESS: at 36.74% examples, 247006 words/s, in_qsize 8, out_qsize 1\n",
      "2018-04-30 20:01:12,373 : INFO : EPOCH 3 - PROGRESS: at 37.11% examples, 246161 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:01:14,430 : INFO : EPOCH 3 - PROGRESS: at 38.32% examples, 247504 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 20:01:15,465 : INFO : EPOCH 3 - PROGRESS: at 38.84% examples, 247801 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:01:16,481 : INFO : EPOCH 3 - PROGRESS: at 39.48% examples, 248872 words/s, in_qsize 7, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:01:17,482 : INFO : EPOCH 3 - PROGRESS: at 39.93% examples, 248804 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:02:07,735 : INFO : EPOCH 3 - PROGRESS: at 68.87% examples, 268337 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:02:13,934 : INFO : EPOCH 3 - PROGRESS: at 72.70% examples, 270885 words/s, in_qsize 8, out_qsize 0\n",
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      "2018-04-30 20:02:28,210 : INFO : EPOCH 3 - PROGRESS: at 79.67% examples, 269528 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:02:29,232 : INFO : EPOCH 3 - PROGRESS: at 80.49% examples, 270486 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:02:30,254 : INFO : EPOCH 3 - PROGRESS: at 81.25% examples, 271314 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:02:31,254 : INFO : EPOCH 3 - PROGRESS: at 81.95% examples, 271933 words/s, in_qsize 7, out_qsize 1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:02:32,282 : INFO : EPOCH 3 - PROGRESS: at 82.36% examples, 271512 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:02:33,334 : INFO : EPOCH 3 - PROGRESS: at 82.83% examples, 271247 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:03:01,162 : INFO : worker thread finished; awaiting finish of 3 more threads\n",
      "2018-04-30 20:03:01,164 : INFO : worker thread finished; awaiting finish of 2 more threads\n",
      "2018-04-30 20:03:01,185 : INFO : worker thread finished; awaiting finish of 1 more threads\n",
      "2018-04-30 20:03:01,188 : INFO : worker thread finished; awaiting finish of 0 more threads\n",
      "2018-04-30 20:03:01,191 : INFO : EPOCH - 3 : training on 70896303 raw words (52228522 effective words) took 187.4s, 278733 effective words/s\n",
      "2018-04-30 20:03:02,242 : INFO : EPOCH 4 - PROGRESS: at 0.47% examples, 244976 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:03:39,998 : INFO : EPOCH 4 - PROGRESS: at 24.01% examples, 322824 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:03:40,999 : INFO : EPOCH 4 - PROGRESS: at 24.60% examples, 322291 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:03:42,007 : INFO : EPOCH 4 - PROGRESS: at 25.13% examples, 321195 words/s, in_qsize 7, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:03:43,008 : INFO : EPOCH 4 - PROGRESS: at 25.49% examples, 318087 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:04:31,605 : INFO : EPOCH 4 - PROGRESS: at 49.31% examples, 284753 words/s, in_qsize 6, out_qsize 0\n",
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      "2018-04-30 20:04:56,015 : INFO : EPOCH 4 - PROGRESS: at 59.40% examples, 270098 words/s, in_qsize 7, out_qsize 1\n",
      "2018-04-30 20:04:56,992 : INFO : EPOCH 4 - PROGRESS: at 59.85% examples, 269907 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:04:58,002 : INFO : EPOCH 4 - PROGRESS: at 60.29% examples, 269523 words/s, in_qsize 7, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:04:59,025 : INFO : EPOCH 4 - PROGRESS: at 60.92% examples, 270045 words/s, in_qsize 8, out_qsize 0\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:06:16,491 : INFO : EPOCH 4 - PROGRESS: at 95.29% examples, 254781 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:06:49,633 : INFO : worker thread finished; awaiting finish of 3 more threads\n",
      "2018-04-30 20:06:49,660 : INFO : worker thread finished; awaiting finish of 2 more threads\n",
      "2018-04-30 20:06:49,672 : INFO : worker thread finished; awaiting finish of 1 more threads\n",
      "2018-04-30 20:06:49,758 : INFO : worker thread finished; awaiting finish of 0 more threads\n",
      "2018-04-30 20:06:49,760 : INFO : EPOCH - 4 : training on 70896303 raw words (52234952 effective words) took 228.6s, 228547 effective words/s\n",
      "2018-04-30 20:06:50,966 : INFO : EPOCH 5 - PROGRESS: at 0.19% examples, 89277 words/s, in_qsize 8, out_qsize 0\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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     ]
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     "output_type": "stream",
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      "2018-04-30 20:12:42,735 : INFO : EPOCH 5 - PROGRESS: at 74.97% examples, 110984 words/s, in_qsize 8, out_qsize 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:12:43,743 : INFO : EPOCH 5 - PROGRESS: at 75.23% examples, 111063 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:12:44,758 : INFO : EPOCH 5 - PROGRESS: at 75.57% examples, 111241 words/s, in_qsize 7, out_qsize 0\n",
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     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-04-30 20:14:01,858 : INFO : EPOCH 5 - PROGRESS: at 94.42% examples, 114096 words/s, in_qsize 7, out_qsize 0\n",
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      "2018-04-30 20:14:19,441 : INFO : EPOCH 5 - PROGRESS: at 98.92% examples, 114959 words/s, in_qsize 8, out_qsize 0\n",
      "2018-04-30 20:14:20,496 : INFO : EPOCH 5 - PROGRESS: at 99.24% examples, 115048 words/s, in_qsize 7, out_qsize 0\n",
      "2018-04-30 20:14:21,538 : INFO : EPOCH 5 - PROGRESS: at 99.67% examples, 115252 words/s, in_qsize 6, out_qsize 0\n",
      "2018-04-30 20:14:22,415 : INFO : worker thread finished; awaiting finish of 3 more threads\n",
      "2018-04-30 20:14:22,429 : INFO : worker thread finished; awaiting finish of 2 more threads\n",
      "2018-04-30 20:14:22,456 : INFO : worker thread finished; awaiting finish of 1 more threads\n",
      "2018-04-30 20:14:22,460 : INFO : worker thread finished; awaiting finish of 0 more threads\n",
      "2018-04-30 20:14:22,463 : INFO : EPOCH - 5 : training on 70896303 raw words (52233652 effective words) took 452.6s, 115416 effective words/s\n",
      "2018-04-30 20:14:22,473 : INFO : training on a 354481515 raw words (261155944 effective words) took 1298.6s, 201102 effective words/s\n",
      "2018-04-30 20:14:22,569 : INFO : saving Word2Vec object under yelp_300features_40minwords_10context, separately None\n",
      "2018-04-30 20:14:22,628 : INFO : storing np array 'vectors' to yelp_300features_40minwords_10context.wv.vectors.npy\n",
      "2018-04-30 20:14:22,906 : INFO : not storing attribute vectors_norm\n",
      "2018-04-30 20:14:23,044 : INFO : storing np array 'syn1neg' to yelp_300features_40minwords_10context.trainables.syn1neg.npy\n",
      "2018-04-30 20:14:23,385 : INFO : not storing attribute cum_table\n",
      "2018-04-30 20:14:31,633 : INFO : saved yelp_300features_40minwords_10context\n"
     ]
    }
   ],
   "source": [
    "# Import the built-in logging module and configure it so that Word2Vec \n",
    "# creates nice output messages\n",
    "import logging\n",
    "logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s',\\\n",
    "    level=logging.INFO)\n",
    "# Set values for various parameters\n",
    "num_features = 300    # Word vector dimensionality                      \n",
    "min_word_count = 5   # Minimum word count                        \n",
    "num_workers = 4       # Number of threads to run in parallel\n",
    "context = 10          # Context window size                                                                                    \n",
    "downsampling = 1e-3   # Downsample setting for frequent words\n",
    "\n",
    "# Initialize and train the model (this will take some time)\n",
    "from gensim.models import word2vec\n",
    "print('training model...')\n",
    "model = word2vec.Word2Vec(sentences, workers=num_workers, \\\n",
    "            size=num_features, min_count = min_word_count, \\\n",
    "            window = context, sample = downsampling)\n",
    "model_name = \"yelp_300features_40minwords_10context\"\n",
    "model.save(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel_launcher.py:1: DeprecationWarning: Call to deprecated `most_similar` (Method will be removed in 4.0.0, use self.wv.most_similar() instead).\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "2018-04-30 20:14:45,435 : INFO : precomputing L2-norms of word weight vectors\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[(u'guy', 0.8088240027427673),\n",
       " (u'gentleman', 0.7590212821960449),\n",
       " (u'dude', 0.7199798822402954),\n",
       " (u'woman', 0.6940141916275024),\n",
       " (u'lady', 0.668986439704895),\n",
       " (u'girl', 0.625653088092804),\n",
       " (u'gentlemen', 0.6141798496246338),\n",
       " (u'gal', 0.5959008932113647),\n",
       " (u'gent', 0.5817946791648865),\n",
       " (u'bouncer', 0.5532838106155396)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.most_similar(\"man\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'medical','safety','healthcare','sanitation','wellbeing','hygiene','violations','wellness','billing','neurological','nutrition','financial','mental','inspectors','environmental','behavioral','illness','accounting','umc','hipaa',"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ipykernel_launcher.py:1: DeprecationWarning: Call to deprecated `most_similar` (Method will be removed in 4.0.0, use self.wv.most_similar() instead).\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "similar_list = model.most_similar(positive=[\"health\"],topn=20)\n",
    "for tupl in similar_list:\n",
    "    print(\"'\",tupl[0],\"'\",\",\",sep='',end='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
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