eea244c479703d1105751196d4fd97cf6476f9bd,src/edu/stanford/nlp/sentiment/SentimentModel.java,SentimentModel,SentimentModel,#RNNOptions#TwoDimensionalSet#Set#,86

Before Change


    this.op = op;
    rand = (op.randomSeed != 0) ? new Random(op.randomSeed) : new Random(); 

    readWordVectors();
    if (op.numHid > 0) {
      this.numHid = op.numHid;
    } else {

After Change


    // TODO: record for posterity the random seed if it was set to 0
    rand = (op.randomSeed != 0) ? new Random(op.randomSeed) : new Random(); 

    if (op.randomWordVectors) {
      initRandomWordVectors(trainingTrees);
    } else {
      readWordVectors();
    }
    if (op.numHid > 0) {
      this.numHid = op.numHid;
    } else {
      int size = 0;
      for (SimpleMatrix vector : wordVectors.values()) {
        size = vector.getNumElements();
        break;
      }
      this.numHid = size;
    }

    TwoDimensionalSet<String, String> binaryProductions = TwoDimensionalSet.hashSet();
    if (op.simplifiedModel) {
      binaryProductions.add("", "");
    } else {
      // TODO
      // figure out what binary productions we have in these trees
      // Note: the current sentiment training data does not actually
      // have any constituent labels
    }

    Set<String> unaryProductions = Generics.newHashSet();
    if (op.simplifiedModel) {
      unaryProductions.add("");
    } else {
      // TODO
      // figure out what unary productions we have in these trees (preterminals only, after the collapsing)