0fa45de729441240384dc044b989aa97e39a6220,src/edu/stanford/nlp/sentiment/SentimentTraining.java,SentimentTraining,main,#String[]#,129

Before Change


    // read in the trees
    List<Tree> trainingTrees = SentimentUtils.readTreesWithGoldLabels(trainPath);
    System.err.println("Read in " + trainingTrees.size() + " training trees");
    List<Tree> devTrees = SentimentUtils.readTreesWithGoldLabels(devPath);
    System.err.println("Read in " + devTrees.size() + " dev trees");

    if (filterNeutral) {
      Filter<Tree> neutralFilter = new Filter<Tree>() {
        public boolean accept(Tree tree) {
          int gold = RNNCoreAnnotations.getGoldClass(tree);
          return gold != 2;
        }
      };
      trainingTrees = CollectionUtils.filterAsList(trainingTrees, neutralFilter);
      devTrees = CollectionUtils.filterAsList(devTrees, neutralFilter);
      System.err.println("Filtered training trees: " + trainingTrees.size());
      System.err.println("Filtered dev trees: " + devTrees.size());
    }

    // TODO: binarize the trees, then collapse the unary chains.

After Change


    // read in the trees
    List<Tree> trainingTrees = SentimentUtils.readTreesWithGoldLabels(trainPath);
    System.err.println("Read in " + trainingTrees.size() + " training trees");
    if (filterNeutral) {
      trainingTrees = CollectionUtils.filterAsList(trainingTrees, NEUTRAL_FILTER);
      System.err.println("Filtered training trees: " + trainingTrees.size());
    }

    List<Tree> devTrees = null;
    if (devPath != null) {
      devTrees = SentimentUtils.readTreesWithGoldLabels(devPath);
      System.err.println("Read in " + devTrees.size() + " dev trees");
      if (filterNeutral) {
        devTrees = CollectionUtils.filterAsList(devTrees, NEUTRAL_FILTER);
        System.err.println("Filtered dev trees: " + devTrees.size());
      }
    }