rnn_scratch.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    从头实现rnn\n",
    "    rnn循环结构"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import csv\n",
    "import nltk\n",
    "import itertools\n",
    "import numpy as np\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#定义一些基本的常量\n",
    "vocabulary_size = 8000\n",
    "unknown_token = \"UNKNOWN_TOKEN\"\n",
    "start_token = \"SENTENCE_START\"\n",
    "end_token = \"SENTENCE_END\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['SENTENCE_START', 'body', 'SENTENCE_END'], ['SENTENCE_START', 'i', 'joined', 'a', 'new', 'league', 'this', 'year', 'and', 'they', 'have', 'different', 'scoring', 'rules', 'than', 'i', \"'m\", 'used', 'to', '.', 'SENTENCE_END'], ['SENTENCE_START', 'it', \"'s\", 'a', 'slight', 'ppr', 'league-', '.2', 'ppr', '.', 'SENTENCE_END'], ['SENTENCE_START', 'standard', 'besides', '1', 'points', 'for', '15', 'yards', 'receiving', ',', '.2', 'points', 'per', 'completion', ',', '6', 'points', 'per', 'td', 'thrown', ',', 'and', 'some', 'bonuses', 'for', 'rec/rush/pass', 'yardage', '.', 'SENTENCE_END'], ['SENTENCE_START', 'my', 'question', 'is', ',', 'is', 'it', 'wildly', 'clear', 'that', 'qb', 'has', 'the', 'highest', 'potential', 'for', 'points', '?', 'SENTENCE_END'], ['SENTENCE_START', 'i', 'put', 'in', 'the', 'rules', 'at', 'a', 'ranking', 'site', 'and', 'noticed', 'that', 'top', 'qbs', 'had', '300', 'points', 'more', 'than', 'the', 'top', 'rb/wr', '.', 'SENTENCE_END'], ['SENTENCE_START', 'would', 'it', 'be', 'dumb', 'not', 'to', 'grab', 'a', 'qb', 'in', 'the', 'first', 'round', '?', 'SENTENCE_END'], ['SENTENCE_START', 'in', 'your', 'scenario', ',', 'a', 'person', 'could', 'just', 'not', 'run', 'the', 'mandatory', 'background', 'check', 'on', 'the', 'buyer', 'and', 'still', 'sell', 'the', 'gun', 'to', 'the', 'felon', '.', 'SENTENCE_END'], ['SENTENCE_START', 'there', \"'s\", 'no', 'way', 'to', 'enforce', 'it', '.', 'SENTENCE_END'], ['SENTENCE_START', 'an', 'honest', 'seller', 'is', 'going', 'to', 'not', 'sell', 'the', 'gun', 'to', 'them', 'when', 'they', 'see', 'they', \"'re\", 'a', 'felon', 'on', 'the', 'background', 'check', '.', 'SENTENCE_END'], ['SENTENCE_START', 'a', 'dishonest', 'seller', 'is', \"n't\", 'going', 'to', 'run', 'the', 'check', 'in', 'the', 'first', 'place', '.', 'SENTENCE_END'], ['SENTENCE_START', 'no', 'one', 'is', 'going', 'to', 'be', 'honest', 'enough', 'to', 'run', 'the', 'check', ',', 'see', 'they', \"'re\", 'a', 'felon', ',', 'and', 'then', 'all', 'of', 'a', 'sudden', 'immediately', 'turn', 'dishonest', 'and', 'say', '``', 'nah', ',', 'you', 'know', 'what', ',', 'here', \"'s\", 'your', 'gun', 'anyway', '.', \"''\", 'SENTENCE_END'], ['SENTENCE_START', 'they', 'would', \"n't\", 'run', 'the', 'fucking', 'check', 'in', 'the', 'first', 'place', ',', 'genius', '.', 'SENTENCE_END'], ['SENTENCE_START', 'your', 'bullshit', 'proposal', 'is', '**not', 'enforceable**', '.', 'SENTENCE_END'], ['SENTENCE_START', 'this', 'is', 'why', 'people', 'without', '&', 'gt', ';', 'here', \"'s\", 'an', 'idea', ',', 'why', 'not', 'make', 'a', 'background', 'check', 'system', 'where', 'it', 'would', 'be', 'illegal', 'to', 'sell', 'guns', 'to', 'felons', '?', 'SENTENCE_END'], ['SENTENCE_START', 'that', 'does', \"n't\", 'convince', 'you', '?', 'SENTENCE_END'], ['SENTENCE_START', 'idgaf', '.', 'SENTENCE_END'], ['SENTENCE_START', 'we', 'already', 'fucking', 'have', 'that', '.', 'SENTENCE_END'], ['SENTENCE_START', 'what', 'are', \"n't\", 'you', 'understanding', 'about', 'this', '?', '!', 'SENTENCE_END'], ['SENTENCE_START', 'it', \"'s\", 'just', 'currently', 'not', 'available', 'to', 'private', 'sellers', '.', 'SENTENCE_END'], ['SENTENCE_START', 'i', \"'d\", 'like', 'to', 'make', 'it', 'available', ',', 'but', 'there', \"'s\", 'no', 'point', 'in', 'making', 'it', 'mandatory', '.', 'SENTENCE_END'], ['SENTENCE_START', '&', 'gt', ';', 'you', \"'re\", 'just', 'supporting', 'it', 'to', 'make', 'a', 'gesture', 'towards', 'background', 'check', 'reform', 'in', 'bad', 'faith', '.', 'SENTENCE_END'], ['SENTENCE_START', 'as', 'a', 'gun', 'owner', 'who', 'has', 'harmed', 'no', 'one', 'and', 'has', 'constitutionally', 'protected', 'rights', ',', 'i', 'actually', 'do', \"n't\", 'own', 'the', 'anti-gun', 'side', 'a', 'damn', 'thing', '.', 'SENTENCE_END'], ['SENTENCE_START', 'it', \"'s\", 'people', 'like', 'you', 'that', 'convince', 'me', 'to', 'not', 'give', 'an', 'inch', 'at', 'all', '.', 'SENTENCE_END'], ['SENTENCE_START', 'i', \"'m\", 'wiling', 'to', 'extend', 'nics', 'to', 'private', 'sellers', 'as', 'voluntary', '.', 'SENTENCE_END'], ['SENTENCE_START', 'take', 'it', 'or', 'leave', 'it', ',', 'because', 'it', 'is', \"n't\", 'going', 'to', 'be', 'made', 'mandatory', '.', 'SENTENCE_END'], ['SENTENCE_START', 'not', 'gon', 'na', 'happen', '.', 'SENTENCE_END'], ['SENTENCE_START', 'period', '.', 'SENTENCE_END'], ['SENTENCE_START', 'they', 'do', \"n't\", 'get', 'paid', 'for', 'how', 'much', 'time', 'you', 'spend', 'building', 'your', 'army', '.', 'SENTENCE_END'], ['SENTENCE_START', 'they', 'get', 'paid', 'when', 'you', 'gem', 'it', '.', 'SENTENCE_END'], ['SENTENCE_START', 'having', 'a', 'premade', 'layout', 'saves', 'what', ',', '30', 'seconds', '?', 'SENTENCE_END'], ['SENTENCE_START', 'during', 'that', 'time', 'they', \"'ve\", 'made', '$', '0', 'and', 'still', 'have', 'the', 'ability', 'to', 'make', '$', 'x', 'if', 'you', 'decide', 'to', 'gem', 'it', '.', 'SENTENCE_END'], ['SENTENCE_START', 'i', 'dunno', ',', 'back', 'before', 'the', 'august', 'update', 'in', 'an', 'a+', 'lobby', 'for', 'tower', 'control', 'in', 'saltspray', 'rig', ',', 'i', 'remember', 'the', 'enemy', 'team', 'barraging', 'us', 'with', 'bombs', 'in', 'a', 'suspiciously', 'coordinated', 'fashion', '.', 'SENTENCE_END'], ['SENTENCE_START', 'and', 'my', 'teammates', 'were', 'also', 'tossing', 'bombs', 'left', 'and', 'right', '.', 'SENTENCE_END'], ['SENTENCE_START', 'non-stop', 'splat/suction/burst', 'bombs', '.', 'SENTENCE_END'], ['SENTENCE_START', 'bombs', ',', 'bombs', 'fucking', 'everywhere', '.', 'SENTENCE_END'], ['SENTENCE_START', 'it', 'was', 'terrifying', 'having', 'to', 'dodge', 'one', 'after', 'the', 'other', '.', 'SENTENCE_END'], ['SENTENCE_START', 'it', 'never', 'ended', ',', 'and', 'some', 'of', 'them', 'even', 'had', 'bomb', 'rush', 'to', 'toss', 'even', 'more', 'goddamn', 'bombs', '.', 'SENTENCE_END'], ['SENTENCE_START', 'i', 'think', 'i', 'still', 'have', 'ptsd', 'of', 'that', 'horrifying', 'event', '.', 'SENTENCE_END'], ['SENTENCE_START', 'that', 'match', 'really', 'felt', 'like', 'a', 'michael', 'bay', 'movie', '.', 'SENTENCE_END'], ['SENTENCE_START', 'no', ',', 'but', 'toriyama', 'sometimes', 'would', 'draw', 'himself', 'as', 'a', 'little', 'robot', '.', 'SENTENCE_END'], ['SENTENCE_START', 'shen', 'was', 'a', 'funny', 'character', 'for', 'a', 'few', 'episodes', '(', 'hitting', 'yamcha', 'in', 'the', 'junk', ')', 'before', 'you', 'find', 'out', 'his', 'true', 'identity', '.', 'SENTENCE_END'], ['SENTENCE_START', 'then', 'he', 'has', 'an', 'awesome', 'fight', 'with', 'piccolo', '.', 'SENTENCE_END'], ['SENTENCE_START', 'implement', 'some', 'form', 'of', 'tenure', 'for', 'mods', 'and', 'require', 'a', 'majority', 'vote', 'to', 'remove', 'any', 'tenured', 'mod', '.', 'SENTENCE_END'], ['SENTENCE_START', 'only', 'allow', 'mods', 'to', 'trigger', 'a', 'removal', 'vote', 'on', 'mods', 'lower', 'than', 'them', 'in', 'the', 'hierarchy', 'however', '.', 'SENTENCE_END'], ['SENTENCE_START', 'this', 'removes', 'the', 'possibility', 'of', 'a', 'single', 'mod', '(', 'such', 'as', 'an', 'absentee', 'top', 'mod', ')', 'swooping', 'in', 'and', 'blowing', 'up', 'the', 'sub', 'but', 'does', \"n't\", 'create', 'opportunities', 'for', 'hijacking', '.', 'SENTENCE_END'], ['SENTENCE_START', 'importantly', ',', 'it', 'also', 'does', \"n't\", 'require', 'rejiggering', 'the', 'existing', 'mod', 'hierarchies', 'or', 'ongoing', 'admin', 'involvement', 'in', 'dispute', 'resolution', '.', 'SENTENCE_END'], ['SENTENCE_START', 'i', 'hate', 'reading', 'shit', 'like', 'this', 'because', 'you', 'sound', 'like', 'such', 'a', 'catch', 'before', 'or', 'after', 'you', 'started', 'working', 'out', ',', 'and', 'your', 'husband', 'takes', 'you', 'for', 'granted', '.', 'SENTENCE_END'], ['SENTENCE_START', 'what', 'i', 'would', 'do', 'to', 'be', 'with', 'someone', 'like', 'you', '.', 'SENTENCE_END'], ['SENTENCE_START', 'i', \"'m\", 'not', 'going', 'to', 'tell', 'you', 'to', 'stay', 'or', 'go', 'but', 'whichever', 'you', 'decide', ',', 'just', 'do', \"n't\", 'lose', 'sight', 'of', 'how', 'you', 'deserve', 'to', 'be', 'treated', 'and', 'do', \"n't\", 'put', 'up', 'with', 'anything', 'less', '.', 'SENTENCE_END']]\n"
     ]
    }
   ],
   "source": [
    "#处理数据，这里的数据是从reddit上面下载的英文的评论，预先使用nltk工具处理后，\n",
    "#得到原始的训练数据集\n",
    "file_path = \"reddit-comments-2015-08.csv\"\n",
    "tokenized = []\n",
    "original = []\n",
    "with open(file_path, 'r') as f:\n",
    "    #读取内容\n",
    "    reader = csv.reader(f, skipinitialspace=True)\n",
    "    for x in reader:\n",
    "        #每个句子前后都加上开始和结束标记，然后再使用nltk分词\n",
    "        sentences = nltk.sent_tokenize(x[0].lower())\n",
    "        for sentence in sentences:\n",
    "            original.append(sentence)\n",
    "            sentence = start_token + \" \" + sentence + \" \" + end_token\n",
    "            tokenized.append(nltk.word_tokenize(sentence))\n",
    "    f.close()\n",
    "print(tokenized[0:50])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['body', \"i joined a new league this year and they have different scoring rules than i'm used to.\"]\n"
     ]
    }
   ],
   "source": [
    "print(original[0:2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 65499 unique words tokens\n"
     ]
    }
   ],
   "source": [
    "#统计词频\n",
    "word_freq = nltk.FreqDist(itertools.chain(*tokenized))\n",
    "print(\"Found {} unique words tokens\".format(len(word_freq)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['SENTENCE_START', 'SENTENCE_END', '.', 'the', ',', 'to', 'i', 'a', 'and', 'of', 'you', 'it', 'that', 'is', 'in', 'for', \"n't\", \"'s\", ')', '(', 'have', 'but', ':', 'on', 'with', 'this', 'be', 'are', 'not', 'do', 'if', 'was', 'they', 'as', '?', 'or', 'my', 'your', 'just', 'so', \"''\", 'like', '[', ']', ';', 'at', 'he', 'can', 'would', '``', 'there', 'what', 'all', 'we', 'about', '&', 'people', 'from', 'more', 'an', 'get', 'me', 'out', 'one', 'up', 'will', \"'m\", 'when', 'because', '!', 'them', 'some', 'no', 'think', 'has', \"'re\", 'by', '-', 'their', 'how', 'any', 'time', 'http', 'really', 'then', 'gt', 'had', 'does', 'who', 'other', 'only', 'than', 'even', 'also', 'his', 'know', '%', 'did', 'good', '*', '...', 'been', 'make', 'could', 'much', \"'ve\", 'which', 'were', 'she', 'should', 'being', 'way', 'see', 'now', 'her', 'want', 'well', 'https', 'game', 'go', 'still', 'him', 'into', 'most', 'going', 'very', 'something', 'too', 'here', 'amp', 'need', 'use', \"'ll\", 'say', 'first', 'am', 'over', 'right', 'why', 'where', \"'d\", 'back', 'work', 'after', 'got', 'same', 'better', 'take', 'lot', 'thing', 'things', 'actually', 'those', 'sure', 'never', 'new', 'off', 'though', 'before', 'please', 'ca', 'these', 'pretty', 'our', '--', 'while', 'someone', 'its', 'down', 'many', 'us', 'since', 'every', '$', 'said', \"'\", '2', '|', 'post', 'point', 'feel', 'probably', 'always', 'look', 'years', 'two', 'around', 'few', '#', 'anything', 'might', 'made', 'play', 'best', 'find', 'try', 'little', 'own', 'may', 'bad', 'getting', 'great', 'different', 'day', 'maybe', 'long', 'through', 'used', 'enough', 'doing', 'give', 'without', 'help', 'both', 'again', 'having', 'last', '3', 'keep', 'put', 'another', 'shit', 'year', 'life', 'love', 'mean', '1', 'money', 'hard', 'let', 'bit', 'part', 'everyone', 'ever', 'least', 'less', 'trying', '**', 'person', 'questions', 'nothing', 'using', 'games', 'reason', 'end', 'come', 'saying', 'makes', 'problem', 'far', 'read', 'either', 'able', 'start', 'stuff', 'against', 'world', 'such', 'already', 'subreddit', 'once', 'making', 'guy', 'each', 'big', 'until', 'question', 'else', 'etc', 'place', 'seems', 'yes', 'done', 'action', 'team', 'contact', 'thought', 'anyone', 'kind', 'wrong', 'old', 'away', 'idea', 'fact', 'bot', 'everything', 'free', 'between', 'times', 'looking', 'high', 'yeah', 'understand', 'friends', '5', 'case', 'real', '^', 'however', 'tell', 'instead', 'believe', 'automatically', 'man', 'level', 'whole', 'show', 'removed', 'comment', 'means', 'gets', 'next', 'top', '4', 'gun', 'thanks', 'women', 'change', 'live', 'moderators', 'playing', 'went', 'days', 'support', 'run', 'fun', 'definitely', 'wo', 'found', 'check', 'rather', 'job', 'video', 'guys', 'issue', 'buy', 'others', 'set', 'seen', 'almost', 'power', 'guess', '’', 'likely', 'nice', 'started', 'players', 'mind', '/message/compose/', 'ask', 'rules', 'agree', 'concerns', 'talking', 'system', 'side', 'experience', 'edit', 'yet', 'fuck', 'story', '*i', 'full', 'fucking', 'damage', 'ago', 'performed', 'matter', 'second', 'small', 'usually', '10', 'left', 'possible', 'week', 'remember', 'care', 'completely', 'control', 'especially', 'unless', 'pay', 'often', 'example', 'true', 'link', 'must', 'stop', 'working', 'issues', 'yourself', 'god', 'myself', 'sense', 'taking', 'wanted', 'home', 'quite', 'looks', 'says', 'talk', 'order', '//www.youtube.com/watch', 'hope', 'thread', 'works', 'easy', 'comes', 'seem', 'number', 'under', 'single', 'state', 'build', 'school', 'months', 'hit', 'men', 'sometimes', 'black', 'family', 'friend', 'sort', 'reddit', 'exactly', 'na', 'name', 'course', 'information', 'based', 'basically', 'thank', 'watch', 'similar', 'sorry', 'player', 'whatever', 'during', 'add', 'worth', 'played', 'opinion', 'fine', 'goes', 'past', 'due', 'came', 'house', 'white', 'kill', 'couple', 'took', 'low', 'line', 'move', 'huge', 'car', 'hours', 'open', 'simply', 'deal', 'ones', 'needs', 'group', 'call', 'hate', 'hand', 'thinking', 'super', 'close', 'oh', 'per', 'leave', 'important', 'happen', 'situation', 'op', 'kids', 'honestly', 'head', 'city', 'called', 'body', '@', 'happy', 'character', 'country', 'title', 'certain', 'entire', 'food', '6', 'turn', '100', 'amount', 'answer', 'area', 'chance', 'told', 'half', 'saw', 'personal', 'current', 'community', 'personally', 'sounds', 'interesting', 'guns', 'season', 'cause', 'learn', 'along', 'type', 'literally', 'tried', 'outside', 'list', 'behind', 'higher', 'cool', 'price', 'face', 'asking', 'running', 'water', 'later', 'content', 'card', 'together', 'obviously', 'lol', 'coming', 'given', 'difference', 'government', 'music', 'submission', 'fight', 'pc', 'wait', 'win', 'account', 'within', 'rest', 'three', 'message', 'source', 'above', 'main', 's', 'weeks', 'happened', 'takes', 'dont', 'class', 'general', 'actual', 'early', 'themselves', 'enjoy', 'sub', 'sound', 'problems', 'month', 'code', 'front', 'public', 'asked', 'whether', 'mostly', 'original', 'wants', 'easily', 'light', 'argument', 'company', 'war', 'anyway', 'future', 'luck', 'heard', 'phone', 'characters', 'consider', 'minutes', 'awesome', 'sex', 'longer', 'de', 'rule', 'business', 'become', 'needed', 'night', 'strong', 'absolutely', 'comments', 'points', 'except', 'hell', 'clear', 'large', 'advice', 'stupid', 'gon', 'word', 'plan', 'today', 'itself', 'series', 'specific', 'seriously', 'generally', 'amazing', 'short', 'wish', 'evidence', 'pick', '20', 'die', 'cost', 'hear', 'drive', 'easier', 'quality', 'version', 'felt', 'stay', 'save', 'mine', 'lost', 'correct', 'weight', 'store', 'posts', 'human', 'hold', 'common', 'value', 'average', 'bring', '+', 'reading', '=', 'allowed', 'party', 'room', 'several', 'happens', 'history', 'normal', 'starting', 'site', 'although', 'plus', 'perfect', 'data', 'relationship', 'd', 'soon', 'girl', 'bought', 'words', 'totally', 'currently', 'lower', 'otherwise', 'base', 'looked', 'lots', 'giving', 'option', 'law', 'feeling', 'imagine', 'book', 'knew', 'cut', 'favorite', 'spend', '/', 'watching', 'parents', 'ok', 'speed', 'result', 'simple', 'living', 'death', 'health', 'building', 'form', 'allow', 'send', 'include', 'image', 'position', 'major', 'dead', 'age', 'reasons', 'alone', 'eat', 'discussion', 'attack', 'hey', 'seeing', 'space', 'towards', 'worked', 'follow', 'process', 'kid', 'sell', 'mods', 'children', 'moment', 'ability', 'weird', '8', 'okay', 'certainly', 'drop', '30', 'woman', 'social', 'interested', 'fast', 'kinda', 'posting', 'im', 'fit', 'range', 'fair', 'paid', 'extra', 'red', 'article', 'poor', 'internet', 'gave', 'recommend', 'focus', '50', 'knows', 'break', 'difficult', 'trade', 'decent', 't', 'changes', 'explain', 'multiple', 'shows', 'clearly', 'ways', 'x', 'movie', 'ass', 'safe', 'expect', 'worse', 'lose', 'items', 'changed', 'fire', 'majority', 'across', 'note', 'meant', 'cards', 'recently', 'taken', 'choice', 'local', 'decided', '15', 'picture', 'late', 'near', 'feels', 'anymore', 'research', 'effect', 'fall', 'page', 'available', 'finally', 'attention', 'google', 'supposed', 'cheap', 'added', 'fan', 'crazy', 'league', 'gone', 'online', 'provide', 'complete', 'special', 'ban', 'act', 'realize', 'style', 'bunch', 'following', '“', 'view', 'report', 'american', 'assume', 'extremely', 'air', 'known', 'himself', 'service', 'telling', 'size', 'legal', 'vs', 'song', 'gives', 'numbers', 'parts', 'text', '**|**', 'force', 'respect', 'mention', 'serious', 'la', 'vote', 'figure', 'total', 'particular', 'quickly', 'item', 'dude', 'videos', 'hour', 'inside', 'further', 'carry', 'moving', 'funny', 'risk', 'buying', '7', 'worst', 'related', 'books', 'rights', 'teams', 'perhaps', 'random', 'shot', 'understanding', 'enemy', 'young', 'putting', 'compared', 'users', 'hopefully', 'unfortunately', 'market', 'mentioned', 'que', 'gaming', 'crime', 'create', 'fans', 'dark', 'child', '”', 'quick', 'terms', 'laws', 'tag', 'claim', 'college', 'training', 'damn', 'ended', 'bigger', 'nobody', 'hands', 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'//www.p0ody-files.com/ff_to_ebook/mobile/makeepub.php', 'teenager', 'purposefully', 'precious', 'handles', 'distant', 'hash', 'graphic', 'ost', 'git', 'capabilities', 'modules', 'ira', 'edgy', 'manipulated', 'practicing', 'rincewind', 'makers', 'lifted', 'clause', 'sane', 'statistically', 'twelve', 'buyout', 'aged', 'witcher', 'p.s', 'len', 'tuition', 'roland', '|average|', 'repairs', 'vg', 'lightly', 'lynch', 'walgreens', 'havent', 'charts', 'grave', 'gospel', 'essay', 'blend', 'scandal', '^^please', 'mvp', 'documented', 'problematic', 'sticky', 'mail-in', 'facility', 'rehabilitation', 'scooter', 'remotely', 'diagnosis', 'psych', 'realised', 'enforced', 'waist', 'pts', 'stafford', 'flames', 'prospects', 'resolved', 'oddly', 'monogamous', 'bets', 'subject=reminder', '0aremindme', 'cata', 'detection', 'vayne', 'adamant', '*do', 'ordinary', 'consistency', 'judges', 'wright', 'programmed', 'processors', 'losses', 'islamic', 'ussr', 'individually', 'starving', 'turrets', 'mules', 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'budgets', 'sarcastic', 'papers', 'disagreeing', 'hermione', 'faint', 'zip', 'payments', 'scores', 'syndrome', 'summers', 'catfish', 'peril', 'comprehend', 'saint', 'tackle', 'interpret', 'wednesday', 'gp', 'dealers', 'regarded', 'ssr', 'mute', 'sich', 'prevented', 'knocking', '2006', 'madden', 'predictable', 'misery', 'whine', 'liverpool', 'tiers', 'contribution', 'consists', 'loading', '980ti', 'sacred', 'на', 'aug', 'что', 'minister', 'auction', 'limiting', 'registration', 'pyro', 'architecture', 'explode', 'sur', 'exotics', 'disappointment', 'tinder', 'laner', 'slam', 'modding', 'shouldnt', '1600', 'kevin', 'yadda', 'mighty', 'discourage', 'vm', 'origins', 'eternity', 'december', 'brooklyn', 'arduino', 'reputable', 'libraries', 'sincerely', 'morals', 'writes', 'taxi', 'anniversary', 'discovery', 'labeling', 'hassle', 'forbid', '50k', 'pockets', 'squeeze', 'celebrate', 'helpless', 'rpg', 'margin', 'backs', 'tougher', 'plague', 'x2', 'perspectives', 'strengths', 'tops', '**click', 'slept', 'highlight', 'flies', 'gamble', 'unicorn', 'kratom', '144hz', 'compact', 'crappy', 'notifications', 'costco', 'bracket', 'integrated', 'satisfy', 'crush', 'invasions', 'glitch', 'trauma', 'treatments', 'hints', 'defenses', 'significance', 'generations', 'indicates', 'a.', 'arizona', 'pleased', 'pops', 'copper', 'quantity', 'scrub', 'merits', 'flop', 'burger', 'citation', 'producers', 'fiscal', 'ob', 'wiped', 'personalities', '//m.youtube.com/watch', 'meantime', 'sandwich', 'rendered', 'cheated', 'inappropriate', 'accusation', 'slipping', 'extract', 'hosts', 'pilots', 'yearly', 'une', 'inflation', 'insulted', 'cope', 'borg', 'moot', '*edit', 'url=http', 'detailing', 'doable', 'retain', 'aunt', 'bridges', 'cease', 'blacks', 'lease', 'refusing', 'psychiatrist', 'directing', 'experimental', 'disadvantage', 'sci', 'emailed', 'eats', 'hilariously', 'expense', 'understands', 'hugs', 'horrific', 'lung', 'linkffn', '^^to', 'twisting', 'challenger', 'dnc', 'relaxing', '38', 'borrow', 'noun', 'protagonist', 'texture', 'kali', 'carb', 'tile', 'vertical', 'flashbacks', 'rekkles', 'cookie', 'armour', 'ineffective', '*status*', '*characters*', '31', 'january', 'chromecast', 'roaming', 'fires', 'tony', 'hacked', 'genetic', 'symptom', 'repo', 'methodology', 'affecting', 'kits', 'vain', 'pile', 'rapidly', 'consume', 'grapes', 'documentation', 'bursts', 'lone', 'discounts', 'inputs', 'holder', '**no', 'current|', 'exotic', 'low-skilled', 'c4', 'fatigue', 'capability', 'imaginable', 'traditions', 'locals', 'mountains', 'tipping', 'tiger', 'rim', 'excluded', 'consulting', 'forgiveness', 'ln', 'slurs', 'agrees', 'repeating', '50+', 'site-wide', 'knights', 'demons', '*this', 'troubles', 'bruce', 'assassin', 'lube', 'premier', 'struggles', 'hallway', 'saber', 'beforehand', 'cookies', 'insecurity', 'functioning', 'maryland', 'gta', 'jp', 'veteran', 'vegetables', '+10', 'vegas', 'dave', 'disbelief', 'globe', '18th', '2001', 'ruining', '//www.wolframalpha.com/input/', 'simon', 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'allergic', 'misinformation', '//steamcommunity.com/sharedfiles/filedetails/', '*do*', 'stretched', 'assembly', 'playstation', 'olive', 'execute', 'tomatoes', 'indicating', 'marshall', 'ak', 'scheduled', 'astral', 'featured', 'theatre', 'dime', 'ser', 'hh', 'gio', 'memes', 'humble', 'ncix', 'intellectually', 'rants', 'irc', 'destination', 'arrives', 'masculine', 'crashing', 'crashes', 'backgrounds', '^the', 'defence', 'oven', 'bake', 'masterpiece', 'warcraft', 'keeper', 'anecdotal', 'endurance', 'riven', 'yasuo', 'bind', 'miracle', 'mastery', 'coaching', 'reign', 'triggered', 'seagate', 'fashioned', 'thc', 'mph', 'booking', 'fanbase', 'contained', 'melted', 'longest', 'annual', 'cousins', 'grandparents', 'procedures', 'gifs', 'arab', 'endgame', 'rifts', 'senses', 'disaster', 'consist', 'gc', 'mb', 'shade', 'possess', 'blake', 'liz', 'bombers', 'toll', 'twisted', 'sweden', 'sacrifices', 'recruits', 'pa', 'doubles', 'db', 'blankets', 'wenger', 'anxious', 'wired', 'proceeds', 'asset', 'dimension', 'shutting', 'plugged', 'thirty', 'unemployed', 'esl', 'foil', 'nostalgia', 'tldr', 'golf', 'torrent', 'varied', 'pussy', 'impress', 'coding', 'xb1', 'dentist', 'proteins', 'smelled', 'clarity', 'forming', 'vancouver', 'asians', 'chemicals', 'tablet', 'promptly', 'cas', 'packet', 'continuity', 'c3', 'peanut', 'fold', 'trait', 'genetics', 'traces', 'pity', 'ironic', 'respectable', 'pale', 'guests', 'judged', 'liquor', 'windshield', '*in', 'playerbase', 'trucks', 'failures', 'concealed', 'lego', 'oppressive', '28randomactsofblowjob+or+randomactsofmuffdive', 'restrict_sr=', 'collecters', 'oppressed', 'favors', '^feedback', 'elderly', 'horn', 'refugee', 'noting', 'myth', 'mmos', 'shelter', 'tomb', 'sind', 'updating', 'studios', '**new', 'subscribe', 'inconsistent', 'networking', 'stickers', 'libido', 'keepers', 'negate', 'momentum', 'cooldowns', 'coolest', 'redundant', 'extending', 'partisan', 'sums', 'scouting', '^to', 'sensible', 'clearing', 'flipped', 'enterprise', 'boil', 'baked', 'rotate', 'innocuous', 'rouge', 'radiator', 'mls', 'nba', 'zwei', 'ggez', 'configuration', 'scrutiny', 'fascist', 'magazines', 'copied', 'doses', 'texts', 'dough', 'hah', 'intriguing', 'itunes', 'että', 'civ', 'v.', 'senator', 'skirt', 'bethesda', 'teleport', 'ceo', 'santa', 'creek', 'pyramid', 'lottery', 'donate', 'overpriced', 'recruiting', 'swing', 'pp', 'wager', 'planted', 'murray', 'lions', 'grateful', 'sober', 'launched', 'consensual', 'tracked', 'oliver', 'recreational', '5k', 'lid', 'happily', 'fathers', 'endorsed', 'acceptance', 'thursday', 'instruction', 'ml', 'showcase', 'presentation', 'liver', 'serves', 'rambling', 'belly', 'packages', 'attach', 'declared', 'hmmm', 'sunlight', 'anecdote', 'malicious', 'doctrine', '/r/mylittlepony/comments/1lwzub/deviantart_imgur_mirror_bot_nightmirrormoon/', '//github.com/meditonsin/nightmirrormoon', 'advocating', 'fortunately', '.i', 'kelly', 'controversy', 'amusing', 'cw', 'fist', 'blatant', 'cosmetics', 'aswell', 'cis', 'feasible', 'poisoning', 'therapists', '1440p', 'midnight', 'reporters', 'charitable', 'obtain', '240', 'irresponsible', '2.2', 'landscape', 'protoss', 'shrimp', 'industries', 'disappeared', 'intensive', 'jewelry', 'lamb', 'goodbye', 'questioning', 'propose', 'rhythm', 'trails', 'homicides', 'visually', 'willingness', 'worded', 'wished', 'thomas', 'andrew', 'evaluation', '20a', 'prohibited', 'props', 'cans', 'robert', 'haircut', 'locking', 'tragic', 'unrealistic', 'to=/r/randomactsofblowjob', 'alan', 'greece', 'basket', 'labs', 'inbox', 'fetish', 'kik', 'internally', 'exercising', 'tragedy', 'insisted', 'eager', 'patented', 'saga', 'weighs', 'punk', '*at', 'admitting', 'unwilling', 'thickness', 'delta', 'listings', 'pie', 'horrified', 'velocity', 'messing', '1080p', 'motherfucker', 'squats', 'cultures', 'buds', 'beloved', 'rescue', 'emily', 'hips', 'academics', 'dressing', 'doom', 'devoted', 'skeptical', 'tales', '**i', 'eaten', 'alphabet', 'dresses', 'sour', 'co', 'fnaf', 'organ', 'vocals', 'hog', 'prize', 'solomon', 'tossed', 'pledge', 'ditch', 'fucker', 'drafted', 'immigrant', 'terrified', 'ksp', 'lan', 'strategic', 'marked', 'rubber', 'weights', 'oak', 'syrup', 'generating', 'paris', 'collected', '3-5', 'unmodified', 'widespread', 'prejudice', 'jerks', 'renting', '960', 'temporarily', '/r/needadvice', 'educate', 'psa', 'apocalypse', 'preferences', 'c-51', 'disappointing', 'expressions', 'uniform', 'athlete', 'blur', 'piano', 'twenty', 'glance', 'toxicity', 'sanity', 'declined', 'expired', '//www.reddit.com/wiki/faq', 'wilson', 'popcorn', 'raffle', 'it..', 'guardians', 'nine', 'carpet', 'configure', 'adventures', 'daddy', 'fulfilled', 'simulator', 'lawsuit', 'looting', 'monetary', 'idle', 'markets', 'administration', 'trunk', 'jailbreak', 'palestinian', 'euros', 'independently', 'ambitious', 'flagged', 'classical', 'crank', 'documentary', 'UNKNOWN_TOKEN']\n"
     ]
    }
   ],
   "source": [
    "#获取常用词，然后构建词频向量\n",
    "vocab = word_freq.most_common(vocabulary_size - 1)\n",
    "index_to_word = [x[0] for x in vocab]\n",
    "index_to_word.append(unknown_token)\n",
    "word_to_index = dict([w, i] for i, w in enumerate(index_to_word))\n",
    "print(index_to_word)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'SENTENCE_START': 0, 'SENTENCE_END': 1, '.': 2, 'the': 3, ',': 4, 'to': 5, 'i': 6, 'a': 7, 'and': 8, 'of': 9, 'you': 10, 'it': 11, 'that': 12, 'is': 13, 'in': 14, 'for': 15, \"n't\": 16, \"'s\": 17, ')': 18, '(': 19, 'have': 20, 'but': 21, ':': 22, 'on': 23, 'with': 24, 'this': 25, 'be': 26, 'are': 27, 'not': 28, 'do': 29, 'if': 30, 'was': 31, 'they': 32, 'as': 33, '?': 34, 'or': 35, 'my': 36, 'your': 37, 'just': 38, 'so': 39, \"''\": 40, 'like': 41, '[': 42, ']': 43, ';': 44, 'at': 45, 'he': 46, 'can': 47, 'would': 48, '``': 49, 'there': 50, 'what': 51, 'all': 52, 'we': 53, 'about': 54, '&': 55, 'people': 56, 'from': 57, 'more': 58, 'an': 59, 'get': 60, 'me': 61, 'out': 62, 'one': 63, 'up': 64, 'will': 65, \"'m\": 66, 'when': 67, 'because': 68, '!': 69, 'them': 70, 'some': 71, 'no': 72, 'think': 73, 'has': 74, \"'re\": 75, 'by': 76, '-': 77, 'their': 78, 'how': 79, 'any': 80, 'time': 81, 'http': 82, 'really': 83, 'then': 84, 'gt': 85, 'had': 86, 'does': 87, 'who': 88, 'other': 89, 'only': 90, 'than': 91, 'even': 92, 'also': 93, 'his': 94, 'know': 95, '%': 96, 'did': 97, 'good': 98, '*': 99, '...': 100, 'been': 101, 'make': 102, 'could': 103, 'much': 104, \"'ve\": 105, 'which': 106, 'were': 107, 'she': 108, 'should': 109, 'being': 110, 'way': 111, 'see': 112, 'now': 113, 'her': 114, 'want': 115, 'well': 116, 'https': 117, 'game': 118, 'go': 119, 'still': 120, 'him': 121, 'into': 122, 'most': 123, 'going': 124, 'very': 125, 'something': 126, 'too': 127, 'here': 128, 'amp': 129, 'need': 130, 'use': 131, \"'ll\": 132, 'say': 133, 'first': 134, 'am': 135, 'over': 136, 'right': 137, 'why': 138, 'where': 139, \"'d\": 140, 'back': 141, 'work': 142, 'after': 143, 'got': 144, 'same': 145, 'better': 146, 'take': 147, 'lot': 148, 'thing': 149, 'things': 150, 'actually': 151, 'those': 152, 'sure': 153, 'never': 154, 'new': 155, 'off': 156, 'though': 157, 'before': 158, 'please': 159, 'ca': 160, 'these': 161, 'pretty': 162, 'our': 163, '--': 164, 'while': 165, 'someone': 166, 'its': 167, 'down': 168, 'many': 169, 'us': 170, 'since': 171, 'every': 172, '$': 173, 'said': 174, \"'\": 175, '2': 176, '|': 177, 'post': 178, 'point': 179, 'feel': 180, 'probably': 181, 'always': 182, 'look': 183, 'years': 184, 'two': 185, 'around': 186, 'few': 187, '#': 188, 'anything': 189, 'might': 190, 'made': 191, 'play': 192, 'best': 193, 'find': 194, 'try': 195, 'little': 196, 'own': 197, 'may': 198, 'bad': 199, 'getting': 200, 'great': 201, 'different': 202, 'day': 203, 'maybe': 204, 'long': 205, 'through': 206, 'used': 207, 'enough': 208, 'doing': 209, 'give': 210, 'without': 211, 'help': 212, 'both': 213, 'again': 214, 'having': 215, 'last': 216, '3': 217, 'keep': 218, 'put': 219, 'another': 220, 'shit': 221, 'year': 222, 'life': 223, 'love': 224, 'mean': 225, '1': 226, 'money': 227, 'hard': 228, 'let': 229, 'bit': 230, 'part': 231, 'everyone': 232, 'ever': 233, 'least': 234, 'less': 235, 'trying': 236, '**': 237, 'person': 238, 'questions': 239, 'nothing': 240, 'using': 241, 'games': 242, 'reason': 243, 'end': 244, 'come': 245, 'saying': 246, 'makes': 247, 'problem': 248, 'far': 249, 'read': 250, 'either': 251, 'able': 252, 'start': 253, 'stuff': 254, 'against': 255, 'world': 256, 'such': 257, 'already': 258, 'subreddit': 259, 'once': 260, 'making': 261, 'guy': 262, 'each': 263, 'big': 264, 'until': 265, 'question': 266, 'else': 267, 'etc': 268, 'place': 269, 'seems': 270, 'yes': 271, 'done': 272, 'action': 273, 'team': 274, 'contact': 275, 'thought': 276, 'anyone': 277, 'kind': 278, 'wrong': 279, 'old': 280, 'away': 281, 'idea': 282, 'fact': 283, 'bot': 284, 'everything': 285, 'free': 286, 'between': 287, 'times': 288, 'looking': 289, 'high': 290, 'yeah': 291, 'understand': 292, 'friends': 293, '5': 294, 'case': 295, 'real': 296, '^': 297, 'however': 298, 'tell': 299, 'instead': 300, 'believe': 301, 'automatically': 302, 'man': 303, 'level': 304, 'whole': 305, 'show': 306, 'removed': 307, 'comment': 308, 'means': 309, 'gets': 310, 'next': 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3929, 'tuesday': 3930, 'deeper': 3931, 'partially': 3932, '+1': 3933, 'horror': 3934, 'hr': 3935, 'coat': 3936, 'btc': 3937, 'structures': 3938, 'quarter': 3939, 'entitled': 3940, 'cigarettes': 3941, 'ignored': 3942, 'garage': 3943, 'albums': 3944, 'distribution': 3945, 'oz': 3946, 'flawed': 3947, 'confederate': 3948, 'grain': 3949, 'hiring': 3950, 'recipe': 3951, '1-2': 3952, 'pot': 3953, 'curve': 3954, 'jedi': 3955, 'mmo': 3956, 'stacks': 3957, 'faced': 3958, 'socialism': 3959, 'gem': 3960, 'minimal': 3961, 'cube': 3962, 'victory': 3963, 'operate': 3964, 'releases': 3965, 'listened': 3966, 'cuts': 3967, 'beauty': 3968, 'invited': 3969, 'holds': 3970, 'secure': 3971, 'guards': 3972, 'involving': 3973, 'lastly': 3974, 'severely': 3975, 'seats': 3976, 'hearts': 3977, 'protein': 3978, 'explore': 3979, 'te': 3980, 'houses': 3981, 'roster': 3982, 'stadium': 3983, 'buttons': 3984, 'paragraph': 3985, 'walls': 3986, 'zombies': 3987, 'liking': 3988, 'animation': 3989, '2.5': 3990, 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'communication': 4051, 'transactions': 4052, 'des': 4053, 'therapy': 4054, 'harmful': 4055, 'ethics': 4056, 'filling': 4057, 'worthy': 4058, 'dass': 4059, 'mit': 4060, 'mechanism': 4061, '**not**': 4062, 'studio': 4063, 'techniques': 4064, 'addressing': 4065, 'carefully': 4066, 'ok.': 4067, 'rope': 4068, 'technique': 4069, 'solved': 4070, 'void': 4071, 'soccer': 4072, 'openly': 4073, 'interviews': 4074, 'strict': 4075, 'evga': 4076, 'motion': 4077, 'legendary': 4078, 'employer': 4079, 'washington': 4080, 'religions': 4081, 'morally': 4082, 'theft': 4083, 'hockey': 4084, 'atleast': 4085, 'payment': 4086, 'carrier': 4087, 'universal': 4088, 'confirm': 4089, 'bubble': 4090, 'ups': 4091, '//redd.it/32u91p': 4092, 'vidilux': 4093, 'em': 4094, 'vanguard': 4095, 'assistance': 4096, 'judging': 4097, 'regions': 4098, 'climb': 4099, 'suitable': 4100, 'url': 4101, 'cuz': 4102, 'deeply': 4103, 'fixing': 4104, 'contrary': 4105, 'properties': 4106, 'extended': 4107, 'acid': 4108, 'hired': 4109, 'grass': 4110, '970': 4111, 'print': 4112, 'pistol': 4113, 'lifetime': 4114, 'completed': 4115, 'to=remindmebot': 4116, 'anytime': 4117, 'exhaust': 4118, 'resource': 4119, 'pirates': 4120, 'television': 4121, 'symbol': 4122, 'qbs': 4123, 'incentive': 4124, 'gifts': 4125, 'wheels': 4126, 'creator': 4127, 'overpowered': 4128, 'messaging': 4129, 'dan': 4130, 'je': 4131, 'unrelated': 4132, 'ratings': 4133, 'h': 4134, 'spin': 4135, 'não': 4136, 'seattle': 4137, 'iraq': 4138, 'fool': 4139, 'ps': 4140, 'complaints': 4141, 'interactions': 4142, 'breakdown': 4143, '**storage**': 4144, 'micro': 4145, 'recommendations': 4146, 'joining': 4147, '600': 4148, 'friendship': 4149, 'eastern': 4150, 'dawn': 4151, 'risks': 4152, 'bow': 4153, 'folder': 4154, 'stones': 4155, 'wording': 4156, 'tolerance': 4157, 'ego': 4158, 'laid': 4159, 'journey': 4160, 'companion': 4161, 'av': 4162, 'monsters': 4163, 'improving': 4164, 'fighters': 4165, 'march': 4166, 'seeking': 4167, 'brazil': 4168, 'confusion': 4169, 'vocal': 4170, 'lvl': 4171, 'stealth': 4172, 'holes': 4173, 'bf': 4174, 'lmao': 4175, 'leaning': 4176, 'glasses': 4177, 'addiction': 4178, 'returns': 4179, 'hobby': 4180, 'tits': 4181, 'pilot': 4182, 'ate': 4183, 'sins': 4184, 'kiss': 4185, 'comp': 4186, 'maintaining': 4187, 'indication': 4188, 'dates': 4189, 'occurs': 4190, 'insert': 4191, 'metric': 4192, 'vet': 4193, 'qualified': 4194, 'injuries': 4195, 'ages': 4196, 'tune': 4197, 'jim': 4198, 'ja': 4199, 'sharking': 4200, 'engineers': 4201, 'arrive': 4202, 'tournament': 4203, 'journalists': 4204, 'corrupt': 4205, 'gaining': 4206, 'welfare': 4207, 'wreck': 4208, 'languages': 4209, 'insult': 4210, 'cheat': 4211, 'xd': 4212, 'gatherer': 4213, 'hills': 4214, 'comfort': 4215, '20post': 4216, 'fury': 4217, 'inches': 4218, 'aircraft': 4219, 'downtown': 4220, 'apparent': 4221, 'hunting': 4222, 'eight': 4223, 'organized': 4224, 'shorter': 4225, 'educated': 4226, 'portal': 4227, 'downvotes': 4228, 'subtle': 4229, 'comics': 4230, 'organizations': 4231, 'tall': 4232, 'lesson': 4233, 'shell': 4234, 'liquid': 4235, 'amd': 4236, 'whatsoever': 4237, 'realizing': 4238, 'scientists': 4239, 'repair': 4240, 'formed': 4241, 'ultra': 4242, 'listentothis': 4243, 'recording': 4244, 'registered': 4245, 'suggests': 4246, 'hunters': 4247, 'commander': 4248, 'tweak': 4249, 'describing': 4250, 'feat': 4251, 'midrange': 4252, 'chief': 4253, 'bid': 4254, 'haki': 4255, 'michael': 4256, 'county': 4257, 'uni': 4258, 'exceptions': 4259, 'thumb': 4260, 'dependent': 4261, 'nightmare': 4262, 'ranged': 4263, 'vaccine': 4264, 'session': 4265, 'bullets': 4266, '6.': 4267, 'villain': 4268, 'heck': 4269, 'kicking': 4270, 'ethical': 4271, 'discount': 4272, 'seven': 4273, 'frustrated': 4274, 'burned': 4275, 'york': 4276, 'impressive': 4277, 'wikipedia': 4278, 'wine': 4279, 'hall': 4280, 'entertaining': 4281, 'lyrics': 4282, 'shopping': 4283, 'mistaken': 4284, 'vendor': 4285, 'defender': 4286, 'rep': 4287, 'impression': 4288, 'pcpartpicker': 4289, 'council': 4290, 'landing': 4291, 'selection': 4292, 'cam': 4293, 'attraction': 4294, 'etc.': 4295, 'sniper': 4296, 'utterly': 4297, 'begins': 4298, 'glory': 4299, '^\\\\': 4300, 'automated': 4301, 'copies': 4302, 'suits': 4303, 'helmet': 4304, 'runes': 4305, 'manually': 4306, 'functions': 4307, 'i7': 4308, 'nvidia': 4309, 'ui': 4310, 'buried': 4311, 'belong': 4312, 'nra': 4313, 'restaurants': 4314, 'neighbors': 4315, 'voices': 4316, 'implemented': 4317, 'tongue': 4318, 'ukraine': 4319, 'courses': 4320, 'cooperation': 4321, 'peak': 4322, 'jeans': 4323, 'paypal': 4324, 'approval': 4325, 'sec': 4326, 'aber': 4327, 'abandoned': 4328, 'compromise': 4329, 'proposed': 4330, 'rooms': 4331, 'buddies': 4332, 'utter': 4333, 'luxury': 4334, 'weekends': 4335, '‘': 4336, 'partners': 4337, 'adjust': 4338, 'sounded': 4339, 'lowest': 4340, '*^': 4341, 'chelsea': 4342, 'categories': 4343, '/r/videos': 4344, 'demands': 4345, 'progression': 4346, 'zones': 4347, 'hungry': 4348, 'comparable': 4349, 'invested': 4350, 'tape': 4351, 'upvotes': 4352, 'stealing': 4353, 'violate': 4354, '//gatherer.wizards.com/handlers/image.ashx': 4355, 'type=card': 4356, '//gatherer.wizards.com/pages/card/details.aspx': 4357, '//magiccards.info/query': 4358, '//www.mtgprice.com/search': 4359, 'contacting': 4360, 'laughed': 4361, 'brush': 4362, 'leveling': 4363, 'singer': 4364, 'answering': 4365, 'mining': 4366, 'accent': 4367, 'releasing': 4368, 'shadows': 4369, 'breathing': 4370, 'periods': 4371, 'noticeable': 4372, 'patterns': 4373, 'slots': 4374, 'sacrifice': 4375, 'npc': 4376, 'conspiracy': 4377, 'bronze': 4378, 'violating': 4379, 'nicotine': 4380, 'token': 4381, 'isaac': 4382, 'adequate': 4383, 'z': 4384, 'ranks': 4385, 'climbing': 4386, '___': 4387, 'holiday': 4388, 'contracts': 4389, 'inherently': 4390, 'processing': 4391, 'processes': 4392, 'mecha': 4393, 'grandma': 4394, 'charging': 4395, 'hurting': 4396, 'macro': 4397, 'slip': 4398, '//offerando.info/football': 4399, 'satisfied': 4400, 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7775, 'pyramid': 7776, 'lottery': 7777, 'donate': 7778, 'overpriced': 7779, 'recruiting': 7780, 'swing': 7781, 'pp': 7782, 'wager': 7783, 'planted': 7784, 'murray': 7785, 'lions': 7786, 'grateful': 7787, 'sober': 7788, 'launched': 7789, 'consensual': 7790, 'tracked': 7791, 'oliver': 7792, 'recreational': 7793, '5k': 7794, 'lid': 7795, 'happily': 7796, 'fathers': 7797, 'endorsed': 7798, 'acceptance': 7799, 'thursday': 7800, 'instruction': 7801, 'ml': 7802, 'showcase': 7803, 'presentation': 7804, 'liver': 7805, 'serves': 7806, 'rambling': 7807, 'belly': 7808, 'packages': 7809, 'attach': 7810, 'declared': 7811, 'hmmm': 7812, 'sunlight': 7813, 'anecdote': 7814, 'malicious': 7815, 'doctrine': 7816, '/r/mylittlepony/comments/1lwzub/deviantart_imgur_mirror_bot_nightmirrormoon/': 7817, '//github.com/meditonsin/nightmirrormoon': 7818, 'advocating': 7819, 'fortunately': 7820, '.i': 7821, 'kelly': 7822, 'controversy': 7823, 'amusing': 7824, 'cw': 7825, 'fist': 7826, 'blatant': 7827, 'cosmetics': 7828, 'aswell': 7829, 'cis': 7830, 'feasible': 7831, 'poisoning': 7832, 'therapists': 7833, '1440p': 7834, 'midnight': 7835, 'reporters': 7836, 'charitable': 7837, 'obtain': 7838, '240': 7839, 'irresponsible': 7840, '2.2': 7841, 'landscape': 7842, 'protoss': 7843, 'shrimp': 7844, 'industries': 7845, 'disappeared': 7846, 'intensive': 7847, 'jewelry': 7848, 'lamb': 7849, 'goodbye': 7850, 'questioning': 7851, 'propose': 7852, 'rhythm': 7853, 'trails': 7854, 'homicides': 7855, 'visually': 7856, 'willingness': 7857, 'worded': 7858, 'wished': 7859, 'thomas': 7860, 'andrew': 7861, 'evaluation': 7862, '20a': 7863, 'prohibited': 7864, 'props': 7865, 'cans': 7866, 'robert': 7867, 'haircut': 7868, 'locking': 7869, 'tragic': 7870, 'unrealistic': 7871, 'to=/r/randomactsofblowjob': 7872, 'alan': 7873, 'greece': 7874, 'basket': 7875, 'labs': 7876, 'inbox': 7877, 'fetish': 7878, 'kik': 7879, 'internally': 7880, 'exercising': 7881, 'tragedy': 7882, 'insisted': 7883, 'eager': 7884, 'patented': 7885, 'saga': 7886, 'weighs': 7887, 'punk': 7888, '*at': 7889, 'admitting': 7890, 'unwilling': 7891, 'thickness': 7892, 'delta': 7893, 'listings': 7894, 'pie': 7895, 'horrified': 7896, 'velocity': 7897, 'messing': 7898, '1080p': 7899, 'motherfucker': 7900, 'squats': 7901, 'cultures': 7902, 'buds': 7903, 'beloved': 7904, 'rescue': 7905, 'emily': 7906, 'hips': 7907, 'academics': 7908, 'dressing': 7909, 'doom': 7910, 'devoted': 7911, 'skeptical': 7912, 'tales': 7913, '**i': 7914, 'eaten': 7915, 'alphabet': 7916, 'dresses': 7917, 'sour': 7918, 'co': 7919, 'fnaf': 7920, 'organ': 7921, 'vocals': 7922, 'hog': 7923, 'prize': 7924, 'solomon': 7925, 'tossed': 7926, 'pledge': 7927, 'ditch': 7928, 'fucker': 7929, 'drafted': 7930, 'immigrant': 7931, 'terrified': 7932, 'ksp': 7933, 'lan': 7934, 'strategic': 7935, 'marked': 7936, 'rubber': 7937, 'weights': 7938, 'oak': 7939, 'syrup': 7940, 'generating': 7941, 'paris': 7942, 'collected': 7943, '3-5': 7944, 'unmodified': 7945, 'widespread': 7946, 'prejudice': 7947, 'jerks': 7948, 'renting': 7949, '960': 7950, 'temporarily': 7951, '/r/needadvice': 7952, 'educate': 7953, 'psa': 7954, 'apocalypse': 7955, 'preferences': 7956, 'c-51': 7957, 'disappointing': 7958, 'expressions': 7959, 'uniform': 7960, 'athlete': 7961, 'blur': 7962, 'piano': 7963, 'twenty': 7964, 'glance': 7965, 'toxicity': 7966, 'sanity': 7967, 'declined': 7968, 'expired': 7969, '//www.reddit.com/wiki/faq': 7970, 'wilson': 7971, 'popcorn': 7972, 'raffle': 7973, 'it..': 7974, 'guardians': 7975, 'nine': 7976, 'carpet': 7977, 'configure': 7978, 'adventures': 7979, 'daddy': 7980, 'fulfilled': 7981, 'simulator': 7982, 'lawsuit': 7983, 'looting': 7984, 'monetary': 7985, 'idle': 7986, 'markets': 7987, 'administration': 7988, 'trunk': 7989, 'jailbreak': 7990, 'palestinian': 7991, 'euros': 7992, 'independently': 7993, 'ambitious': 7994, 'flagged': 7995, 'classical': 7996, 'crank': 7997, 'documentary': 7998, 'UNKNOWN_TOKEN': 7999}\n"
     ]
    }
   ],
   "source": [
    "print(word_to_index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vacabulary size 8000\n",
      "The least frequent word in our vocabulary is 'documentary' and appeared times 10\n"
     ]
    }
   ],
   "source": [
    "print(\"vacabulary size {}\".format(vocabulary_size))\n",
    "print(\"The least frequent word in our vocabulary is '{}' and appeared times {}\".format(vocab[-1][0], vocab[-1][1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Example sentence:i joined a new league this year and they have different scoring rules than i'm used to.\n",
      "after pre-processint:['SENTENCE_START', 'i', 'joined', 'a', 'new', 'league', 'this', 'year', 'and', 'they', 'have', 'different', 'scoring', 'rules', 'than', 'i', \"'m\", 'used', 'to', '.', 'SENTENCE_END']\n"
     ]
    }
   ],
   "source": [
    "#将所有不在词汇表中的词替换为unknown token\n",
    "for i, sent in enumerate(tokenized):\n",
    "    tokenized[i] = [w if w in word_to_index else unknown_token for w in sent]\n",
    "print(\"Example sentence:{}\".format(original[1]))\n",
    "print(\"after pre-processint:{}\".format(tokenized[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 6, 3494, 7, 155, 795, 25, 222, 8, 32, 20, 202, 4954, 350, 91, 6, 66, 207, 5, 2]\n",
      "[6, 3494, 7, 155, 795, 25, 222, 8, 32, 20, 202, 4954, 350, 91, 6, 66, 207, 5, 2, 1]\n"
     ]
    }
   ],
   "source": [
    "#创建训练数据\n",
    "#训练的主要目的是预测下一个词，所以x的数据是对应y数据的前一个词\n",
    "x_train = np.asarray([[word_to_index[w] for w in sent[:-1]] for sent in tokenized])\n",
    "y_train = np.asarray([[word_to_index[w] for w in sent[1:]] for sent in tokenized])\n",
    "print(x_train[1])\n",
    "print(y_train[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    数据准备好后开始构建RNN网络\n",
    "    首先设置RNN网络的默认参数\n",
    "    网址<a href=\"https://songhuiming.github.io/pages/2017/08/20/build-recurrent-neural-network-from-scratch\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#隐层神经元个数\n",
    "hidden_dim = 100\n",
    "#梯度下降批数\n",
    "bptt_truncate = 1000\n",
    "#s = tanh(ux + w(s-1))\n",
    "#o = softmax(vs)\n",
    "u = np.random.uniform(-np.sqrt(1/vocabulary_size), np.sqrt(1/vocabulary_size), (hidden_dim, vocabulary_size))\n",
    "v = np.random.uniform(-np.sqrt(1/hidden_dim), np.sqrt(1/hidden_dim), (vocabulary_size, hidden_dim))\n",
    "w = np.random.uniform(-np.sqrt(1/hidden_dim), np.sqrt(1/hidden_dim), (hidden_dim, hidden_dim))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#前向传播计算结果\n",
    "#softmax函数是计算x矩阵每一个x的softmax函数值\n",
    "def softmax(x):\n",
    "    xt = np.exp(x - np.sum(np.fromiter(x, \"float\")))\n",
    "    return xt / np.sum(np.fromiter(xt, \"float\"))\n",
    "\n",
    "def forward_propagation(x):\n",
    "    global u, v, w\n",
    "    T = len(x)\n",
    "    s = np.zeros((T + 1, hidden_dim))\n",
    "    s[-1] = np.zeros(hidden_dim)\n",
    "    o = np.zeros((T, vocabulary_size))\n",
    "    \n",
    "    for t in np.arange(T):\n",
    "        s[t] = np.tanh(u[:,x[t]] + w.dot(s[t - 1]))\n",
    "        o[t] = softmax(v.dot(s[t]))\n",
    "    return (o, s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#预测函数\n",
    "#根据o输出值中最大概率的判断结果\n",
    "def prediction(x):\n",
    "    o, s = forward_propagation(x)\n",
    "    return np.argmax(o, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#损失函数\n",
    "#定义交叉熵损失函数\n",
    "#单个token的预测结果熵，对于一个x预测有y类结果，y大小为词库大小\n",
    "def calculate_loss(x, y):\n",
    "    L = 0\n",
    "    for t in np.arange(len(y)):\n",
    "        o, s = forward_propagation(x[t])\n",
    "        correct_word_predictions = o[np.arange(len(y[t])), x[t]]\n",
    "        L += -1 * np.sum(np.fromiter((np.log(correct_word_predictions)), \"float\"))\n",
    "    return L \n",
    "\n",
    "#计算总的，就是把每一个token的熵都加起来\n",
    "def total_loss(x, y):\n",
    "    n = np.sum(np.fromiter((len(y_i) for y_i in y), \"float\"))\n",
    "    return calculate_loss(x, y) / n\n",
    "# print(\"expected loss : {},actual loss : {}\".format(np.log(vocabulary_size), total_loss(x_train[:1000], y_train[:1000])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#反向传播训练模型\n",
    "#使用梯度下降法\n",
    "#因为是循环神经网络，网络中的参数记录有时序信息，所以递推公式中包含有前面的数据信息\n",
    "def bptt(x, y):\n",
    "    global u, v, w\n",
    "    T = len(y)\n",
    "    o, s = forward_propagation(x)\n",
    "    #初始化参数\n",
    "    dLdu = np.zeros(u.shape)\n",
    "    dLdv = np.zeros(v.shape)\n",
    "    dLdw = np.zeros(w.shape)\n",
    "    #初始化参数\n",
    "    delta_o = o \n",
    "    #y^ = y^ - y\n",
    "    delta_o[np.arange(len(y)), y] -= 1\n",
    "    for t in np.arange(T):\n",
    "        dLdv += np.outer(delta_o[t], s[t].T)\n",
    "        delta_t = v.T.dot(delta_o[t]) * (1 - (s[t] * s[t]))\n",
    "        #根据公式从后往前推\n",
    "        for bptt_step in np.arange(max(0, t - bptt_truncate), t + 1)[::-1]:\n",
    "            dLdw += np.outer(delta_t, s[bptt_step - 1])\n",
    "            dLdu[:, x[bptt_step]] += delta_t\n",
    "            delta_t = w.T.dot(delta_t) * (1 - s[bptt_step - 1] * s[bptt_step - 1])\n",
    "    return (dLdu, dLdv, dLdw)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#梯度更新\n",
    "def sgd_step(x, y, learning_rate):\n",
    "    dLdu, dLdv, dLdw = bptt(x, y)\n",
    "    global u, v, w\n",
    "    u -= learning_rate * dLdu\n",
    "    v -= learning_rate * dLdv\n",
    "    w -= learning_rate * dLdw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#模型训练\n",
    "def train_with_sgd(x_train, y_train, learning_rate = 0.005, nepoch = 100, evaluate_loss_after = 5):\n",
    "    losses = []\n",
    "    num_examples_seen = 0 \n",
    "    for epoch in range(nepoch):\n",
    "        if epoch % evaluate_loss_after == 0:\n",
    "            loss = total_loss(x_train, y_train)\n",
    "            losses.append((num_examples_seen, loss))\n",
    "            time = datetime.datetime.now().strftime(\"%Y-%m-%d %H:%M:%S\")\n",
    "            print(\"{} loss after num_examples_seen={} epoch={}:{}\".format(time, num_examples_seen, epoch, loss))\n",
    "            if (len(losses) > 1 and losses[-1][1] > losses[-2][1]):\n",
    "                learning_rate = learning_rate * 0.5\n",
    "                print(\"setting learning rate to {}\".format(learning_rate))\n",
    "        for i in range(len(y_train)):\n",
    "            sgd_step(x_train[i], y_train[i], learning_rate)\n",
    "            num_examples_seen += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019-09-01 18:25:25 loss after num_examples_seen=0 epoch=0:8.9872068821151\n",
      "2019-09-01 18:25:35 loss after num_examples_seen=100 epoch=1:8.98552615293417\n",
      "2019-09-01 18:25:45 loss after num_examples_seen=200 epoch=2:8.983090642311604\n",
      "2019-09-01 18:25:55 loss after num_examples_seen=300 epoch=3:8.977366760876784\n",
      "2019-09-01 18:26:05 loss after num_examples_seen=400 epoch=4:7.4244368431676975\n",
      "2019-09-01 18:26:15 loss after num_examples_seen=500 epoch=5:6.625243664967802\n",
      "2019-09-01 18:26:25 loss after num_examples_seen=600 epoch=6:6.331072642659455\n",
      "2019-09-01 18:26:34 loss after num_examples_seen=700 epoch=7:6.168752788451529\n",
      "2019-09-01 18:26:44 loss after num_examples_seen=800 epoch=8:6.071442979663433\n",
      "2019-09-01 18:26:54 loss after num_examples_seen=900 epoch=9:6.0117639310193445\n"
     ]
    }
   ],
   "source": [
    "losses = train_with_sgd(x_train[:100], y_train[:100], nepoch = 10, evaluate_loss_after = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#使用训练好的模型生成随机新文本\n",
    "def generate_text(dict_words, index_of_words):\n",
    "    #dict_words时type list,index of words 是type dict\n",
    "    sent = [index_of_words[start_token]]\n",
    "    #根据start_token预测后面的词，直到句子的结束\n",
    "    while not sent[-1] == index_of_words[end_token]:\n",
    "        next_probs, _ = forward_propagation(sent)\n",
    "        sample_word = index_of_words[unknown_token]\n",
    "        \n",
    "        #前向预测概率后，取概率最大的单词\n",
    "        while sample_word == index_of_words[unknown_token]:\n",
    "            samples = np.random.multinomial(1, next_probs[-1])\n",
    "            sample_word = np.argmax(samples)\n",
    "        sent.append(sample_word)\n",
    "        \n",
    "    new_sent = [dict_words[i] for i in sent[1:-1]]\n",
    "    new_sent_str = ' '.join(new_sent)\n",
    "    \n",
    "    return new_sent_str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "generate sentence:relations be efficiently think single .\n"
     ]
    }
   ],
   "source": [
    "sent_str = generate_text(index_to_word, word_to_index)\n",
    "print(\"generate sentence:{}\".format(sent_str))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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