testcrf4.java

mallet是自然语言处理、机器学习领域的一个开源项目。

		doTestSpacePrediction (false, false, false);
	}

  public void testSerialization()
  {
    doTestSpacePrediction(false, true, true);
  }

	public void testDenseSerialization ()
	{
		doTestSpacePrediction(false, true, false);
	}

  public void testTokenAccuracy ()
  {
    Pipe p = makeSpacePredictionPipe ();

    InstanceList instances = new InstanceList(p);
    instances.add(new ArrayIterator(data));
    InstanceList[] lists = instances.split (new Random (777), new double[]{.5, .5});

    CRF4 crf = new CRF4(p.getDataAlphabet(), p.getTargetAlphabet());
    crf.addFullyConnectedStatesForLabels();
		crf.setUseSparseWeights (true);

    crf.train (lists[0]);

    TokenAccuracyEvaluator eval = new TokenAccuracyEvaluator ();
    eval.test (crf, lists[1], "Testing", null);

    assertEquals (0.9409, eval.getLastAccuracy (), 0.001);

  }
	public void testPrint ()
	{
		Pipe p = new SerialPipes (new Pipe[] {
       new CharSequence2TokenSequence("."),
			 new TokenText(),
			 new TestCRFTokenSequenceRemoveSpaces(),
			 new TokenSequence2FeatureVectorSequence(),
			 new PrintInputAndTarget(),
    });
		InstanceList one = new InstanceList (p);
		String[] data = new String[] { "ABCDE", };
		one.add (new ArrayIterator (data));
		CRF4 crf = new CRF4 (p, null);
		crf.addFullyConnectedStatesForThreeQuarterLabels(one);
		crf.setWeightsDimensionAsIn (one);
		CRF4.MaximizableCRF mcrf = crf.getMaximizableCRF(one);
		double[] params = new double[mcrf.getNumParameters()];
		for (int i = 0; i < params.length; i++) {
			params [i] = i;
		}
		mcrf.setParameters (params);
		crf.print ();
	}

	public void testCopyStatesAndWeights ()
	{
		Pipe p = new SerialPipes (new Pipe[] {
       new CharSequence2TokenSequence("."),
			 new TokenText(),
			 new TestCRFTokenSequenceRemoveSpaces(),
			 new TokenSequence2FeatureVectorSequence(),
			 new PrintInputAndTarget(),
    });
		InstanceList one = new InstanceList (p);
		String[] data = new String[] { "ABCDE", };
		one.add (new ArrayIterator (data));
		CRF4 crf = new CRF4 (p, null);
		crf.addFullyConnectedStatesForLabels();
		crf.setWeightsDimensionAsIn (one);
		CRF4.MaximizableCRF mcrf = crf.getMaximizableCRF(one);
		double[] params = new double[mcrf.getNumParameters()];
		for (int i = 0; i < params.length; i++) {
			params [i] = i;
		}
		mcrf.setParameters (params);

    StringWriter out = new StringWriter ();
		crf.print (new PrintWriter (out, true));

    CRF4 crf2 = new CRF4 (crf);
    StringWriter out2 = new StringWriter ();
    crf2.print (new PrintWriter (out2, true));

    assertEquals (out.toString(), out2.toString ());

    double val1 = mcrf.getValue ();
    double val2 = crf2.getMaximizableCRF (one).getValue ();
    assertEquals (val1, val2, 1e-5);
	}

  static String toy = "A a\nB b\nC c\nD d\nB b\nC c\n";
  
  public void testStartState ()
  {
    Pipe p = new SerialPipes (new Pipe[]{
      new LineGroupString2TokenSequence (),
      new TokenSequenceMatchDataAndTarget (Pattern.compile ("^(\\S+) (.*)"), 2, 1),
      new TokenSequenceParseFeatureString (false),
      new TokenText (),
      new TokenSequence2FeatureVectorSequence (true, false),
      new Target2LabelSequence (),
      new PrintInputAndTarget (),
    });

    InstanceList data = new InstanceList (p);
    data.add (new LineGroupIterator (new StringReader (toy), Pattern.compile ("\n"), true));

    CRF4 crf = new CRF4 (p, null);
    crf.print();
    crf.addStatesForLabelsConnectedAsIn (data);
    crf.addStartState ();

    Maximizable.ByGradient maxable = crf.getMaximizableCRF (data);
    assertEquals (-1.3862, maxable.getValue (), 1e-4);

    crf = new CRF4 (p, null);
    crf.addOrderNStates (data, new int[] { 1 }, null, "A", null, null, false);
    crf.print();

    maxable = crf.getMaximizableCRF (data);
    assertEquals (-3.09104245335831, maxable.getValue (), 1e-4);
  }

  // Tests that setWeightsDimensionDensely respects featureSelections
  public void testDenseFeatureSelection ()
  {
     Pipe p = makeSpacePredictionPipe ();

     InstanceList instances = new InstanceList (p);
     instances.add (new ArrayIterator(data));

    // Test that dense observations wights aren't added for "default-feature" edges.
    CRF4 crf1 = new CRF4 (p, null);
    crf1.addOrderNStates (instances, new int[] { 0 }, null, "start", null, null, true);
    crf1.setUseSparseWeights (false);
    crf1.train (instances, null, null, null, 1); // Set weights dimension
    int nParams1 = crf1.getMaximizableCRF (instances).getNumParameters ();

    CRF4 crf2 = new CRF4 (p, null);
    crf2.addOrderNStates (instances, new int[] { 0, 1 }, new boolean[] {false, true}, "start", null, null, true);
    crf2.setUseSparseWeights (false);
    crf2.train (instances, null, null, null, 1); // Set weights dimension
    int nParams2 = crf2.getMaximizableCRF (instances).getNumParameters ();

    assertEquals (nParams2, nParams1 + 4);

  }

  public void testXis ()
  {
    Pipe p = makeSpacePredictionPipe ();

    InstanceList instances = new InstanceList (p);
    instances.add (new ArrayIterator(data));

    CRF4 crf1 = new CRF4 (p, null);
    crf1.addFullyConnectedStatesForLabels ();
    crf1.train (instances, null, null, null, 10); // Let's get some parameters

    Instance inst = instances.getInstance (0);
    Sequence input = (Sequence)inst.getData();
    Transducer.Lattice lattice = crf1.forwardBackward (input, (Sequence)inst.getTarget(),
                                                       false, true, null);
    for (int ip = 0; ip < lattice.length()-1; ip++) {
      for (int i = 0; i < crf1.numStates (); i++) {
        Transducer.State state = crf1.getState (i);
        Transducer.TransitionIterator it = state.transitionIterator (input, ip);
        double gamma = lattice.getGammaProbability (ip, state);
        double xiSum = 0;
        while (it.hasNext()) {
          Transducer.State dest = it.nextState ();
          double xi = lattice.getXiProbability (ip, state, dest);
          xiSum += xi;
        }
        assertEquals (gamma, xiSum, 1e-5);
      }
    }
  }

  public static Test suite ()
  {
    return new TestSuite (TestCRF4.class);
  }

  public void testStateAddWeights ()
  {
    Pipe p = TestMEMM.makeSpacePredictionPipe ();
    InstanceList training = new InstanceList (p);
    training.add (new ArrayIterator (TestMEMM.data));

    CRF4 crf = new CRF4 (p, null);
    crf.addFullyConnectedStatesForLabels ();
    crf.train (training);

    // Check that the notstart state is used at test time
    Sequence input = (Sequence) training.getInstance (0).getData ();
    Sequence output = crf.viterbiPath (input).output ();

    boolean notstartFound = false;
    for (int i = 0; i < output.size(); i++) {
      if (output.get(i).toString().equals ("notstart")) {
        notstartFound = true;
      }
    }
    assertTrue (notstartFound);

    // Now add infinite cost onto a transition, and make sure that it's honored.
    CRF4.State state = crf.getState ("notstart");
    int widx = crf.getWeightsIndex ("BadBad");
    SparseVector w = new SparseVector (new double[250]);
    w.setAll (Double.NEGATIVE_INFINITY);
    crf.setWeights (widx, w);

    state.addWeight (0, "BadBad");
    state.addWeight (1, "BadBad");

    // Verify that this effectively prevents the notstart state from being used
    output = crf.viterbiPath (input).output ();
    notstartFound = false;
    for (int i = 0; i < output.size() - 1; i++) {
      if (output.get(i).toString().equals ("notstart")) {
        notstartFound = true;
      }
    }
    assertTrue (!notstartFound);
  }

  private static String oldCrfFile = "test/edu/umass/cs/mallet/base/fst/crf.cnl03.ser.gz";
  private static String testString = "John NNP B-NP O\nDoe NNP I-NP O\nsaid VBZ B-VP O\nhi NN B-NP O\n";

  public void testOldCrf ()
  {
    CRF4 crf = (CRF4) FileUtils.readObject (new File (oldCrfFile));
    Instance inst = new Instance (testString, null, null, null, crf.getInputPipe ());
    Sequence output = crf.transduce ((Sequence) inst.getData ());
    String std = output.toString ();
    assertEquals (" B-PER I-PER O O", std);
  }

  public static void main(String[] args)
  {
		TestSuite theSuite;
		if (args.length > 0) {
			theSuite = new TestSuite();
			for (int i = 0; i < args.length; i++) {
				theSuite.addTest (new TestCRF4 (args [i]));
			}
		} else {
			theSuite = (TestSuite) suite();
		}
		
		junit.textui.TestRunner.run (theSuite);
  }

}