Examples with NNMaster ml.shifu.shifu.core.dtrain.nn.NNMaster used on opensource projects

Example 1 with NNMaster

use of ml.shifu.shifu.core.dtrain.nn.NNMaster in project shifu by ShifuML.

the class NNModelSpecTest method testModelFitIn.

@Test
public void testModelFitIn() {
    PersistorRegistry.getInstance().add(new PersistBasicFloatNetwork());
    BasicML basicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model5.nn")));
    BasicNetwork basicNetwork = (BasicNetwork) basicML;
    FlatNetwork flatNetwork = basicNetwork.getFlat();
    BasicML extendedBasicML = BasicML.class.cast(EncogDirectoryPersistence.loadObject(new File("src/test/resources/model/model6.nn")));
    BasicNetwork extendedBasicNetwork = (BasicNetwork) extendedBasicML;
    FlatNetwork extendedFlatNetwork = extendedBasicNetwork.getFlat();
    NNMaster master = new NNMaster();
    Set<Integer> fixedWeightIndexSet = master.fitExistingModelIn(flatNetwork, extendedFlatNetwork, Arrays.asList(new Integer[] { 1, 2, 3 }));
    Assert.assertEquals(fixedWeightIndexSet.size(), 931);
    fixedWeightIndexSet = master.fitExistingModelIn(flatNetwork, extendedFlatNetwork, Arrays.asList(new Integer[] { 1, 2, 3 }), false);
    Assert.assertEquals(fixedWeightIndexSet.size(), 910);
}

Example 2 with NNMaster

use of ml.shifu.shifu.core.dtrain.nn.NNMaster 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);
}