bert-text-tokenizer.js

// This is an edited version of this file: https://github.com/tensorflow/tfjs-models/blob/master/qna/src/bert_tokenizer.ts
// It's for the LiT text model.

/*
  Example usage:
  
    let tokenizer = await import("./bert-text-tokenizer.js").then(m => new m.BertTokenizer());
    await tokenizer.load();
    let textTokens = tokenizer.tokenize("hello world!");
    textTokens.length = 16
    textTokens = [...textTokens.slice(0, 16)].map(e => e == undefined ? 0 : e); // pad with zeros to length of 16
    textTokens = Int32Array.from(textTokens);
    
*/

/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
const SEPERATOR = '\u2581';
export const UNK_INDEX = 100;
export const CLS_INDEX = 101;
export const CLS_TOKEN = '[CLS]';
export const SEP_INDEX = 102;
export const SEP_TOKEN = '[SEP]';
export const NFKC_TOKEN = 'NFKC';
// export const VOCAB_BASE = 'https://tfhub.dev/tensorflow/tfjs-model/mobilebert/1/';
// export const VOCAB_URL = VOCAB_BASE + 'processed_vocab.json?tfjs-format=file';

/**
 * Class for represent node for token parsing Trie data structure.
 */
class TrieNode {
  constructor(key) {
    this.key = key;
    this.children = {};
    this.end = false;
  }
  getWord() {
    const output = [];
    let node = this;
    while (node != null) {
      if (node.key != null) {
        output.unshift(node.key);
      }
      node = node.parent;
    }
    return [output, this.score, this.index];
  }
}
class Trie {
  constructor() {
    this.root = new TrieNode(null);
  }
  /**
   * Insert the bert vacabulary word into the trie.
   * @param word word to be inserted.
   * @param score word score.
   * @param index index of word in the bert vocabulary file.
   */
  insert(word, score, index) {
    let node = this.root;
    const symbols = [];
    for (const symbol of word) {
      symbols.push(symbol);
    }
    for (let i = 0; i < symbols.length; i++) {
      if (node.children[symbols[i]] == null) {
        node.children[symbols[i]] = new TrieNode(symbols[i]);
        node.children[symbols[i]].parent = node;
      }
      node = node.children[symbols[i]];
      if (i === symbols.length - 1) {
        node.end = true;
        node.score = score;
        node.index = index;
      }
    }
  }
  /**
   * Find the Trie node for the given token, it will return the first node that
   * matches the subtoken from the beginning of the token.
   * @param token string, input string to be searched.
   */
  find(token) {
    let node = this.root;
    let iter = 0;
    while (iter < token.length && node != null) {
      node = node.children[token[iter]];
      iter++;
    }
    return node;
  }
}
function isWhitespace(ch) {
  return /\s/.test(ch);
}
function isInvalid(ch) {
  return (ch.charCodeAt(0) === 0 || ch.charCodeAt(0) === 0xfffd);
}
const punctuations = '[~`!@#$%^&*(){}[];:"\'<,.>?/\\|-_+=';
/** To judge whether it's a punctuation. */
function isPunctuation(ch) {
  return punctuations.indexOf(ch) !== -1;
}
/**
 * Tokenizer for Bert.
 */
const defaultVocab = ["[PAD]","[unused0]","[unused1]","[unused2]","[unused3]","[unused4]","[unused5]","[unused6]","[unused7]","[unused8]","[unused9]","[unused10]","[unused11]","[unused12]","[unused13]","[unused14]","[unused15]","[unused16]","[unused17]","[unused18]","[unused19]","[unused20]","[unused21]","[unused22]","[unused23]","[unused24]","[unused25]","[unused26]","[unused27]","[unused28]","[unused29]","[unused30]","[unused31]","[unused32]","[unused33]","[unused34]","[unused35]","[unused36]","[unused37]","[unused38]","[unused39]","[unused40]","[unused41]","[unused42]","[unused43]","[unused44]","[unused45]","[unused46]","[unused47]","[unused48]","[unused49]","[unused50]","[unused51]","[unused52]","[unused53]","[unused54]","[unused55]","[unused56]","[unused57]","[unused58]","[unused59]","[unused60]","[unused61]","[unused62]","[unused63]","[unused64]","[unused65]","[unused66]","[unused67]","[unused68]","[unused69]","[unused70]","[unused71]","[unused72]","[unused73]","[unused74]","[unused75]","[unused76]","[unused77]","[unused78]","[unused79]","[unused80]","[unused81]","[unused82]","[unused83]","[unused84]","[unused85]","[unused86]","[unused87]","[unused88]","[unused89]","[unused90]","[unused91]","[unused92]","[unused93]","[unused94]","[unused95]","[unused96]","[unused97]","[unused98]","[UNK]","[CLS]","[SEP]","[MASK]","[unused99]","[unused100]","[unused101]","[unused102]","[unused103]","[unused104]","[unused105]","[unused106]","[unused107]","[unused108]","[unused109]","[unused110]","[unused111]","[unused112]","[unused113]","[unused114]","[unused115]","[unused116]","[unused117]","[unused118]","[unused119]","[unused120]","[unused121]","[unused122]","[unused123]","[unused124]","[unused125]","[unused126]","[unused127]","[unused128]","[unused129]","[unused130]","[unused131]","[unused132]","[unused133]","[unused134]","[unused135]","[unused136]","[unused137]","[unused138]","[unused139]","[unused140]","[unused141]","[unused142]","[unused143]","[unused144]","[unused145]","[unused146]","[unused147]","[unused148]","[unused149]","[unused150]","[unused151]","[unused152]","[unused153]","[unused154]","[unused155]","[unused156]","[unused157]","[unused158]","[unused159]","[unused160]","[unused161]","[unused162]","[unused163]","[unused164]","[unused165]","[unused166]","[unused167]","[unused168]","[unused169]","[unused170]","[unused171]","[unused172]","[unused173]","[unused174]","[unused175]","[unused176]","[unused177]","[unused178]","[unused179]","[unused180]","[unused181]","[unused182]","[unused183]","[unused184]","[unused185]","[unused186]","[unused187]","[unused188]","[unused189]","[unused190]","[unused191]","[unused192]","[unused193]","[unused194]","[unused195]","[unused196]","[unused197]","[unused198]","[unused199]","[unused200]","[unused201]","[unused202]","[unused203]","[unused204]","[unused205]","[unused206]","[unused207]","[unused208]","[unused209]","[unused210]","[unused211]","[unused212]","[unused213]","[unused214]","[unused215]","[unused216]","[unused217]","[unused218]","[unused219]","[unused220]","[unused221]","[unused222]","[unused223]","[unused224]","[unused225]","[unused226]","[unused227]","[unused228]","[unused229]","[unused230]","[unused231]","[unused232]","[unused233]","[unused234]","[unused235]","[unused236]","[unused237]","[unused238]","[unused239]","[unused240]","[unused241]","[unused242]","[unused243]","[unused244]","[unused245]","[unused246]","[unused247]","[unused248]","[unused249]","[unused250]","[unused251]","[unused252]","[unused253]","[unused254]","[unused255]","[unused256]","[unused257]","[unused258]","[unused259]","[unused260]","[unused261]","[unused262]","[unused263]","[unused264]","[unused265]","[unused266]","[unused267]","[unused268]","[unused269]","[unused270]","[unused271]","[unused272]","[unused273]","[unused274]","[unused275]","[unused276]","[unused277]","[unused278]","[unused279]","[unused280]","[unused281]","[unused282]","[unused283]","[unused284]","[unused285]","[unused286]","[unused287]","[unused288]","[unused289]","[unused290]","[unused291]","[unused292]","[unused293]","[unused294]","[unused295]","[unused296]","[unused297]","[unused298]","[unused299]","[unused300]","[unused301]","[unused302]","[unused303]","[unused304]","[unused305]","[unused306]","[unused307]","[unused308]","[unused309]","[unused310]","[unused311]","[unused312]","[unused313]","[unused314]","[unused315]","[unused316]","[unused317]","[unused318]","[unused319]","[unused320]","[unused321]","[unused322]","[unused323]","[unused324]","[unused325]","[unused326]","[unused327]","[unused328]","[unused329]","[unused330]","[unused331]","[unused332]","[unused333]","[unused334]","[unused335]","[unused336]","[unused337]","[unused338]","[unused339]","[unused340]","[unused341]","[unused342]","[unused343]","[unused344]","[unused345]","[unused346]","[unused347]","[unused348]","[unused349]","[unused350]","[unused351]","[unused352]","[unused353]","[unused354]","[unused355]","[unused356]","[unused357]","[unused358]","[unused359]","[unused360]","[unused361]",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export class BertTokenizer {
  /**
   * Load the vacabulary file and initialize the Trie for lookup.
   */
  async load(vocabUrl) {
    this.vocab = await this.loadVocab(vocabUrl);
    this.trie = new Trie();
    // Actual tokens start at 999.
    for (let vocabIndex = 999; vocabIndex < this.vocab.length; vocabIndex++) {
      const word = this.vocab[vocabIndex];
      this.trie.insert(word, 1, vocabIndex);
    }
  }
  async loadVocab(url) {
    if(!url) return defaultVocab;
    return fetch(VOCAB_URL).then(d => d.json());
  }
  processInput(text) {
    const charOriginalIndex = [];
    const cleanedText = this.cleanText(text, charOriginalIndex);
    const origTokens = cleanedText.split(' ');
    let charCount = 0;
    const tokens = origTokens.map((token) => {
      token = token.toLowerCase();
      const tokens = this.runSplitOnPunc(token, charCount, charOriginalIndex);
      charCount += token.length + 1;
      return tokens;
    });
    let flattenTokens = [];
    for (let index = 0; index < tokens.length; index++) {
      flattenTokens = flattenTokens.concat(tokens[index]);
    }
    return flattenTokens;
  }
  /* Performs invalid character removal and whitespace cleanup on text. */
  cleanText(text, charOriginalIndex) {
    const stringBuilder = [];
    let originalCharIndex = 0, newCharIndex = 0;
    for (const ch of text) {
      // Skip the characters that cannot be used.
      if (isInvalid(ch)) {
        originalCharIndex += ch.length;
        continue;
      }
      if(isWhitespace(ch)) {
        if(stringBuilder.length > 0 &&
          stringBuilder[stringBuilder.length - 1] !== ' ') {
          stringBuilder.push(' ');
          charOriginalIndex[newCharIndex] = originalCharIndex;
          originalCharIndex += ch.length;
        }
        else {
          originalCharIndex += ch.length;
          continue;
        }
      }
      else {
        stringBuilder.push(ch);
        charOriginalIndex[newCharIndex] = originalCharIndex;
        originalCharIndex += ch.length;
      }
      newCharIndex++;
    }
    return stringBuilder.join('');
  }
  /* Splits punctuation on a piece of text. */
  runSplitOnPunc(text, count, charOriginalIndex) {
    const tokens = [];
    let startNewWord = true;
    for(const ch of text) {
      if (isPunctuation(ch)) {
        tokens.push({ text: ch, index: charOriginalIndex[count] });
        count += ch.length;
        startNewWord = true;
      }
      else {
        if (startNewWord) {
          tokens.push({ text: '', index: charOriginalIndex[count] });
          startNewWord = false;
        }
        tokens[tokens.length - 1].text += ch;
        count += ch.length;
      }
    }
    return tokens;
  }
  /**
   * Generate tokens for the given vocalbuary.
   * @param text text to be tokenized.
   */
  tokenize(text) {
    // Source:
    // https://github.com/google-research/bert/blob/88a817c37f788702a363ff935fd173b6dc6ac0d6/tokenization.py#L311
    let outputTokens = [];
    const words = this.processInput(text);
    words.forEach(word => {
      if(word.text !== CLS_TOKEN && word.text !== SEP_TOKEN) {
        word.text = `${SEPERATOR}${word.text.normalize(NFKC_TOKEN)}`;
      }
    });
    for(let i = 0; i < words.length; i++) {
      const chars = [];
      for (const symbol of words[i].text) {
        chars.push(symbol);
      }
      let isUnknown = false;
      let start = 0;
      const subTokens = [];
      const charsLength = chars.length;
      while(start < charsLength) {
        let end = charsLength;
        let currIndex;
        while(start < end) {
          const substr = chars.slice(start, end).join('');
          const match = this.trie.find(substr);
          if(match != null && match.end != null) {
              currIndex = match.getWord()[2];
              break;
          }
          end = end - 1;
        }
        if(currIndex == null) {
          isUnknown = true;
          break;
        }
        subTokens.push(currIndex);
        start = end;
      }
      if(isUnknown) {
        outputTokens.push(UNK_INDEX);
      } else {
        outputTokens = outputTokens.concat(subTokens);
      }
    }
    return outputTokens;
  }
}
export async function loadTokenizer() {
  const tokenizer = new BertTokenizer();
  await tokenizer.load();
  return tokenizer;
}