Examples with BasicNetwork org.encog.neural.networks.BasicNetwork used on opensource projects

Example 11 with BasicNetwork

use of org.encog.neural.networks.BasicNetwork in project shifu by ShifuML.

the class NNTrainerTest method computeScore.

private void computeScore(File modelFile, MLDataPair dataPair0, MLDataPair dataPair1, MLDataPair dataPair2, MLDataPair dataPair3) {
    BasicNetwork model = (BasicNetwork) EncogDirectoryPersistence.loadObject(modelFile);
    System.out.println((int) (model.compute(dataPair0.getInput()).getData(0) * 1000));
    System.out.println((int) (model.compute(dataPair1.getInput()).getData(0) * 1000));
    System.out.println((int) (model.compute(dataPair2.getInput()).getData(0) * 1000));
    System.out.println((int) (model.compute(dataPair3.getInput()).getData(0) * 1000));
}

Example 12 with BasicNetwork

use of org.encog.neural.networks.BasicNetwork in project shifu by ShifuML.

the class DTrainTest method setup.

@BeforeTest
public void setup() {
    network = new BasicNetwork();
    network.addLayer(new BasicLayer(DTrainTest.INPUT_COUNT));
    network.addLayer(new BasicLayer(DTrainTest.HIDDEN_COUNT));
    network.addLayer(new BasicLayer(DTrainTest.OUTPUT_COUNT));
    network.getStructure().finalizeStructure();
    network.reset();
    weights = network.getFlat().getWeights();
    training = RandomTrainingFactory.generate(1000, 10000, INPUT_COUNT, OUTPUT_COUNT, -1, 1);
}

Example 13 with BasicNetwork

use of org.encog.neural.networks.BasicNetwork in project shifu by ShifuML.

the class NNModelSpecTest method testModelStructureCompare.

@Test
public void testModelStructureCompare() {
    BasicML basicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model0.nn")));
    BasicNetwork basicNetwork = (BasicNetwork) basicML;
    FlatNetwork flatNetwork = basicNetwork.getFlat();
    BasicML extendedBasicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model1.nn")));
    BasicNetwork extendedBasicNetwork = (BasicNetwork) extendedBasicML;
    FlatNetwork extendedFlatNetwork = extendedBasicNetwork.getFlat();
    Assert.assertEquals(new NNStructureComparator().compare(flatNetwork, extendedFlatNetwork), -1);
    Assert.assertEquals(new NNStructureComparator().compare(flatNetwork, flatNetwork), 0);
    Assert.assertEquals(new NNStructureComparator().compare(extendedFlatNetwork, flatNetwork), 1);
    BasicML diffBasicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model2.nn")));
    BasicNetwork diffBasicNetwork = (BasicNetwork) diffBasicML;
    FlatNetwork diffFlatNetwork = diffBasicNetwork.getFlat();
    Assert.assertEquals(new NNStructureComparator().compare(flatNetwork, diffFlatNetwork), -1);
    Assert.assertEquals(new NNStructureComparator().compare(diffFlatNetwork, flatNetwork), -1);
    Assert.assertEquals(new NNStructureComparator().compare(extendedFlatNetwork, diffFlatNetwork), 1);
    Assert.assertEquals(new NNStructureComparator().compare(diffFlatNetwork, extendedFlatNetwork), -1);
    BasicML deepBasicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model3.nn")));
    BasicNetwork deppBasicNetwork = (BasicNetwork) deepBasicML;
    FlatNetwork deepFlatNetwork = deppBasicNetwork.getFlat();
    Assert.assertEquals(new NNStructureComparator().compare(deepFlatNetwork, flatNetwork), 1);
    Assert.assertEquals(new NNStructureComparator().compare(flatNetwork, deepFlatNetwork), -1);
}

Example 14 with BasicNetwork

use of org.encog.neural.networks.BasicNetwork in project shifu by ShifuML.

the class NNModelSpecTest method testFitExistingModelIn.

@Test
public void testFitExistingModelIn() {
    BasicML basicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model0.nn")));
    BasicNetwork basicNetwork = (BasicNetwork) basicML;
    FlatNetwork flatNetwork = basicNetwork.getFlat();
    NNMaster master = new NNMaster();
    Set<Integer> fixedWeightIndexSet = master.fitExistingModelIn(flatNetwork, flatNetwork, Arrays.asList(new Integer[] { 6 }));
    List<Integer> indexList = new ArrayList<Integer>(fixedWeightIndexSet);
    Collections.sort(indexList);
    Assert.assertEquals(indexList.size(), 31);
    fixedWeightIndexSet = master.fitExistingModelIn(flatNetwork, flatNetwork, Arrays.asList(new Integer[] { 1 }));
    indexList = new ArrayList<Integer>(fixedWeightIndexSet);
    Collections.sort(indexList);
    Assert.assertEquals(indexList.size(), 930);
    BasicML extendedBasicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model1.nn")));
    BasicNetwork extendedBasicNetwork = (BasicNetwork) extendedBasicML;
    FlatNetwork extendedFlatNetwork = extendedBasicNetwork.getFlat();
    fixedWeightIndexSet = master.fitExistingModelIn(flatNetwork, extendedFlatNetwork, Arrays.asList(new Integer[] { 1 }));
    indexList = new ArrayList<Integer>(fixedWeightIndexSet);
    Collections.sort(indexList);
    Assert.assertEquals(indexList.size(), 930);
    fixedWeightIndexSet = master.fitExistingModelIn(flatNetwork, extendedFlatNetwork, Arrays.asList(new Integer[] { 1 }), false);
    indexList = new ArrayList<Integer>(fixedWeightIndexSet);
    Collections.sort(indexList);
    Assert.assertEquals(indexList.size(), 900);
}