Examples with NeuralLayer org.kie.dmg.pmml.pmml_4_2.descr.NeuralLayer used on opensource projects

Example 1 with NeuralLayer

use of org.kie.dmg.pmml.pmml_4_2.descr.NeuralLayer in project drools by kiegroup.

the class PMMLGenerationTest method testNNGenration.

@Test
public void testNNGenration() {
    PMML net = PMMLGeneratorUtils.generateSimpleNeuralNetwork(modelName, inputfieldNames, outputfieldNames, inputMeans, inputStds, outputMeans, outputStds, hiddenSize, weights);
    assertNotNull(net);
    ByteArrayOutputStream baos = new ByteArrayOutputStream();
    assertTrue(PMMLGeneratorUtils.streamPMML(net, baos));
    ByteArrayInputStream bais = new ByteArrayInputStream(baos.toByteArray());
    PMML4Compiler compiler = new PMML4Compiler();
    SchemaFactory sf = SchemaFactory.newInstance(XMLConstants.W3C_XML_SCHEMA_NS_URI);
    try {
        Schema schema = sf.newSchema(Thread.currentThread().getContextClassLoader().getResource(compiler.SCHEMA_PATH));
        schema.newValidator().validate(new StreamSource(bais));
    } catch (SAXException e) {
        fail(e.getMessage());
    } catch (IOException e) {
        fail(e.getMessage());
    }
    PMML net2 = null;
    try {
        bais.reset();
        JAXBContext ctx = JAXBContext.newInstance(PMML.class.getPackage().getName());
        net2 = (PMML) ctx.createUnmarshaller().unmarshal(bais);
    } catch (JAXBException e) {
        e.printStackTrace();
    }
    assertNotNull(net2);
    assertEquals(inputfieldNames.length + outputfieldNames.length, net2.getDataDictionary().getDataFields().size());
    assertEquals(net.getDataDictionary().getDataFields().size(), net2.getDataDictionary().getDataFields().size());
    NeuralNetwork n1 = (NeuralNetwork) net.getAssociationModelsAndBaselineModelsAndClusteringModels().get(0);
    NeuralNetwork n2 = (NeuralNetwork) net2.getAssociationModelsAndBaselineModelsAndClusteringModels().get(0);
    assertEquals(n1.getExtensionsAndNeuralLayersAndNeuralInputs().size(), n2.getExtensionsAndNeuralLayersAndNeuralInputs().size());
    assertEquals(6, n2.getExtensionsAndNeuralLayersAndNeuralInputs().size());
    NeuralLayer l1 = (NeuralLayer) n1.getExtensionsAndNeuralLayersAndNeuralInputs().get(3);
    NeuralLayer l2 = (NeuralLayer) n2.getExtensionsAndNeuralLayersAndNeuralInputs().get(3);
    assertEquals(l1.getNeurons().get(4).getCons().get(2).getWeight(), l2.getNeurons().get(4).getCons().get(2).getWeight(), 1e-9);
    assertEquals(weights[(inputfieldNames.length + 1) * 4 + 3], l2.getNeurons().get(4).getCons().get(2).getWeight(), 1e-9);
}

Example 2 with NeuralLayer

use of org.kie.dmg.pmml.pmml_4_2.descr.NeuralLayer in project drools by kiegroup.

the class PMMLGenerationTest method testNNGenration.

@Test
public void testNNGenration() {
    PMML net = PMMLGeneratorUtils.generateSimpleNeuralNetwork(modelName, inputfieldNames, outputfieldNames, inputMeans, inputStds, outputMeans, outputStds, hiddenSize, weights);
    assertNotNull(net);
    ByteArrayOutputStream baos = new ByteArrayOutputStream();
    assertTrue(PMMLGeneratorUtils.streamPMML(net, baos));
    ByteArrayInputStream bais = new ByteArrayInputStream(baos.toByteArray());
    PMML4Compiler compiler = new PMML4Compiler();
    SchemaFactory sf = SchemaFactory.newInstance(XMLConstants.W3C_XML_SCHEMA_NS_URI);
    try {
        Schema schema = sf.newSchema(Thread.currentThread().getContextClassLoader().getResource(compiler.SCHEMA_PATH));
        schema.newValidator().validate(new StreamSource(bais));
    } catch (SAXException e) {
        fail(e.getMessage());
    } catch (IOException e) {
        fail(e.getMessage());
    }
    PMML net2 = null;
    try {
        bais.reset();
        JAXBContext ctx = JAXBContext.newInstance(PMML.class.getPackage().getName());
        net2 = (PMML) ctx.createUnmarshaller().unmarshal(bais);
    } catch (JAXBException e) {
        e.printStackTrace();
    }
    assertNotNull(net2);
    assertEquals(inputfieldNames.length + outputfieldNames.length, net2.getDataDictionary().getDataFields().size());
    assertEquals(net.getDataDictionary().getDataFields().size(), net2.getDataDictionary().getDataFields().size());
    NeuralNetwork n1 = (NeuralNetwork) net.getAssociationModelsAndBaselineModelsAndClusteringModels().get(0);
    NeuralNetwork n2 = (NeuralNetwork) net2.getAssociationModelsAndBaselineModelsAndClusteringModels().get(0);
    assertEquals(n1.getExtensionsAndNeuralLayersAndNeuralInputs().size(), n2.getExtensionsAndNeuralLayersAndNeuralInputs().size());
    assertEquals(6, n2.getExtensionsAndNeuralLayersAndNeuralInputs().size());
    NeuralLayer l1 = (NeuralLayer) n1.getExtensionsAndNeuralLayersAndNeuralInputs().get(3);
    NeuralLayer l2 = (NeuralLayer) n2.getExtensionsAndNeuralLayersAndNeuralInputs().get(3);
    assertEquals(l1.getNeurons().get(4).getCons().get(2).getWeight(), l2.getNeurons().get(4).getCons().get(2).getWeight(), 1e-9);
    assertEquals(weights[(inputfieldNames.length + 1) * 4 + 3], l2.getNeurons().get(4).getCons().get(2).getWeight(), 1e-9);
}