Examples of edu.stanford.nlp.trees.Treebank$CounterTreeProcessor

edu.stanford.nlp.trees.Treebank
A Treebank object provides access to a corpus of examples with given tree structures. This class now implements the Collection interface. However, it may offer less than the full power of the Collection interface: some Treebanks are read only, and so may throw the UnsupportedOperationException. @author Christopher Manning @author Roger Levy (added encoding variable and method)


    if (trainTreebankPath != null) {
      // TODO: make the transformer a member of the model?
      TreeTransformer transformer = buildTrainTransformer(dvparser.getOp());


      Treebank treebank = dvparser.getOp().tlpParams.memoryTreebank();;
      treebank.loadPath(trainTreebankPath, trainTreebankFilter);
      treebank = treebank.transform(transformer);
      System.err.println("Read in " + treebank.size() + " trees from " + trainTreebankPath);


      CacheParseHypotheses cacher = new CacheParseHypotheses(dvparser.parser);
      CacheParseHypotheses.CacheProcessor processor = new CacheParseHypotheses.CacheProcessor(cacher, lexparser, dvparser.op.trainOptions.dvKBest, transformer);
      for (Tree tree : treebank) {
        trainSentences.add(tree);
        trainCompressedParses.put(tree, processor.process(tree).second);
        //System.out.println(tree);
      }


      System.err.println("Finished parsing " + treebank.size() + " trees, getting " + dvparser.op.trainOptions.dvKBest + " hypotheses each");
    }


    if ((runTraining || runGradientCheck) && filter) {
      System.err.println("Filtering rules for the given training set");
      dvparser.dvModel.setRulesForTrainingSet(trainSentences, trainCompressedParses);
      System.err.println("Done filtering rules; " + dvparser.dvModel.numBinaryMatrices + " binary matrices, " + dvparser.dvModel.numUnaryMatrices + " unary matrices, " + dvparser.dvModel.wordVectors.size() + " word vectors");
    }


    //dvparser.dvModel.printAllMatrices();


    Treebank testTreebank = null;
    if (testTreebankPath != null) {
      System.err.println("Reading in trees from " + testTreebankPath);
      if (testTreebankFilter != null) {
        System.err.println("Filtering on " + testTreebankFilter);
      }
      testTreebank = dvparser.getOp().tlpParams.memoryTreebank();;
      testTreebank.loadPath(testTreebankPath, testTreebankFilter);
      System.err.println("Read in " + testTreebank.size() + " trees for testing");
    }


//    runGradientCheck= true;
    if (runGradientCheck) {
      System.err.println("Running gradient check on " + trainSentences.size() + " trees");

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    return index;
  }


  public static void main(String[] args) {
    // simple testing code
    Treebank treebank = new DiskTreebank();
    CategoryWordTag.suppressTerminalDetails = true;
    treebank.loadPath(args[0]);
    final HeadFinder chf = new NoPunctuationHeadFinder();
    treebank.apply(pt -> {
      pt.percolateHeads(chf);
      pt.pennPrint();
      System.out.println();
    });
  }

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    return op;
  }


  public Treebank readTreebank(String treebankPath, FileFilter treebankFilter) {
    System.err.println("Loading trees from " + treebankPath);
    Treebank treebank = op.tlpParams.memoryTreebank();
    treebank.loadPath(treebankPath, treebankFilter);
    System.err.println("Read in " + treebank.size() + " trees from " + treebankPath);
    return treebank;
  }

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      System.exit(-1);
    }
    // Command line options
    Language language = Language.valueOf(args[0]);
    TreebankLangParserParams tlpp = Languages.getLanguageParams(language);
    Treebank trainTreebank = tlpp.diskTreebank();
    trainTreebank.loadPath(args[2]);
    Treebank devTreebank = tlpp.diskTreebank();
    devTreebank.loadPath(args[3]);
    MorphoFeatureSpecification morphoSpec;
    Options options = getOptions(language);
    if (language.equals(Language.Arabic)) {
      morphoSpec = new ArabicMorphoFeatureSpecification();
      String[] languageOptions = {"-arabicFactored"};

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    System.err.println("Read in " + treebank.size() + " trees from " + treebankPath);
    return treebank;
  }


  public List<Tree> readBinarizedTreebank(String treebankPath, FileFilter treebankFilter) {
    Treebank treebank = readTreebank(treebankPath, treebankFilter);
    List<Tree> binarized = binarizeTreebank(treebank, op);
    System.err.println("Converted trees to binarized format");
    return binarized;
  }

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    transitionTimer.done("Converting trees into transition lists");
    System.err.println("Number of transitions: " + transitionIndex.size());


    Random random = new Random(op.trainOptions.randomSeed);


    Treebank devTreebank = null;
    if (devTreebankPath != null) {
      devTreebank = readTreebank(devTreebankPath.first(), devTreebankPath.second());
    }


    PerceptronModel newModel = new PerceptronModel(this.op, transitionIndex, knownStates, rootStates, rootOnlyStates);

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    //parser.outputStats();


    if (testTreebankPath != null) {
      System.err.println("Loading test trees from " + testTreebankPath.first());
      Treebank testTreebank = parser.op.tlpParams.memoryTreebank();
      testTreebank.loadPath(testTreebankPath.first(), testTreebankPath.second());
      System.err.println("Loaded " + testTreebank.size() + " trees");


      EvaluateTreebank evaluator = new EvaluateTreebank(parser.op, null, parser);
      evaluator.testOnTreebank(testTreebank);


      // System.err.println("Input tree: " + tree);

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    CacheParseHypotheses cacher = new CacheParseHypotheses(parser);
    TreeTransformer transformer = DVParser.buildTrainTransformer(parser.getOp());
    List<Tree> sentences = new ArrayList<Tree>();
    for (Pair<String, FileFilter> description : treebanks) {
      System.err.println("Reading trees from " + description.first);
      Treebank treebank = parser.getOp().tlpParams.memoryTreebank();
      treebank.loadPath(description.first, description.second);


      treebank = treebank.transform(transformer);
      sentences.addAll(treebank);
    }


    System.err.println("Processing " + sentences.size() + " trees");

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    Options op = new Options(tlpParams);
    TreeAnnotator ta = new TreeAnnotator(tlpParams.headFinder(), tlpParams, op);


    System.err.println("Reading Trees...");
    FileFilter trainFilter = new NumberRangesFileFilter(args[1], true);
    Treebank trainTreebank = tlpParams.memoryTreebank();
    trainTreebank.loadPath(args[0], trainFilter);


    System.err.println("Annotating trees...");
    Collection<Tree> trainTrees = new ArrayList<Tree>();
    for (Tree tree : trainTreebank) {
      trainTrees.add(ta.transformTree(tree));
    }
    trainTreebank = null; // saves memory


    System.err.println("Training lexicon...");


    Index<String> wordIndex = new HashIndex<String>();
    Index<String> tagIndex = new HashIndex<String>();
    int featureLevel = DEFAULT_FEATURE_LEVEL;
    if (args.length > 3) {
      featureLevel = Integer.parseInt(args[3]);
    }
    ChineseMaxentLexicon lex = new ChineseMaxentLexicon(op, wordIndex, tagIndex, featureLevel);
    lex.initializeTraining(trainTrees.size());
    lex.train(trainTrees);
    lex.finishTraining();


    System.err.print("Testing");


    FileFilter testFilter = new NumberRangesFileFilter(args[2], true);
    Treebank testTreebank = tlpParams.memoryTreebank();
    testTreebank.loadPath(args[0], testFilter);
    List<TaggedWord> testWords = new ArrayList<TaggedWord>();
    for (Tree t : testTreebank) {
      for (TaggedWord tw : t.taggedYield()) {
        testWords.add(tw);
      }

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      combinedParser.saveParserToSerialized(modelPath);
    } else {
      throw new IllegalArgumentException("Need to specify -model to load an already prepared CombinedParser");
    }


    Treebank testTreebank = null;
    if (testTreebankPath != null) {
      System.err.println("Reading in trees from " + testTreebankPath);
      if (testTreebankFilter != null) {
        System.err.println("Filtering on " + testTreebankFilter);
      }
      testTreebank = combinedParser.getOp().tlpParams.memoryTreebank();;
      testTreebank.loadPath(testTreebankPath, testTreebankFilter);
      System.err.println("Read in " + testTreebank.size() + " trees for testing");


      EvaluateTreebank evaluator = new EvaluateTreebank(combinedParser.getOp(), null, combinedParser);
      evaluator.testOnTreebank(testTreebank);
    }
  }

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