Examples with ObjectMapper org.nd4j.shade.jackson.databind.ObjectMapper used on opensource projects

Example 11 with ObjectMapper

use of org.nd4j.shade.jackson.databind.ObjectMapper in project deeplearning4j by deeplearning4j.

the class TestComponentSerialization method assertSerializable.

private static void assertSerializable(Component component) throws Exception {
    ObjectMapper om = new ObjectMapper();
    String json = om.writeValueAsString(component);
    Component fromJson = om.readValue(json, Component.class);
    //Yes, this is a bit hacky, but lombok equal method doesn't seem to work properly for List<double[]> etc
    assertEquals(component.toString(), fromJson.toString());
}

Example 12 with ObjectMapper

use of org.nd4j.shade.jackson.databind.ObjectMapper in project deeplearning4j by deeplearning4j.

the class TestComponentSerialization method assertSerializable.

private static void assertSerializable(Style style) throws Exception {
    ObjectMapper om = new ObjectMapper();
    String json = om.writeValueAsString(style);
    Style fromJson = om.readValue(json, Style.class);
    //Yes, this is a bit hacky, but lombok equal method doesn't seem to work properly for List<double[]> etc
    assertEquals(style.toString(), fromJson.toString());
}

Example 13 with ObjectMapper

use of org.nd4j.shade.jackson.databind.ObjectMapper in project deeplearning4j by deeplearning4j.

the class TestCustomActivation method testCustomActivationFn.

@Test
public void testCustomActivationFn() {
    //First: Ensure that the CustomActivation class is registered
    ObjectMapper mapper = NeuralNetConfiguration.mapper();
    AnnotatedClass ac = AnnotatedClass.construct(IActivation.class, mapper.getSerializationConfig().getAnnotationIntrospector(), null);
    Collection<NamedType> types = mapper.getSubtypeResolver().collectAndResolveSubtypes(ac, mapper.getSerializationConfig(), mapper.getSerializationConfig().getAnnotationIntrospector());
    boolean found = false;
    for (NamedType nt : types) {
        System.out.println(nt);
        if (nt.getType() == CustomActivation.class)
            found = true;
    }
    assertTrue("CustomActivation: not registered with NeuralNetConfiguration mapper", found);
    //Second: let's create a MultiLayerCofiguration with one, and check JSON and YAML config actually works...
    MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder().learningRate(0.1).list().layer(0, new DenseLayer.Builder().nIn(10).nOut(10).activation(new CustomActivation()).build()).layer(1, new OutputLayer.Builder(LossFunctions.LossFunction.MCXENT).nIn(10).nOut(10).build()).pretrain(false).backprop(true).build();
    String json = conf.toJson();
    String yaml = conf.toYaml();
    System.out.println(json);
    MultiLayerConfiguration confFromJson = MultiLayerConfiguration.fromJson(json);
    assertEquals(conf, confFromJson);
    MultiLayerConfiguration confFromYaml = MultiLayerConfiguration.fromYaml(yaml);
    assertEquals(conf, confFromYaml);
}

Example 14 with ObjectMapper

use of org.nd4j.shade.jackson.databind.ObjectMapper in project deeplearning4j by deeplearning4j.

the class Hdf5Archive method readAttributeAsJson.

/**
     * Read JSON-formatted string attribute.
     *
     * @param attribute     HDF5 attribute to read as JSON formatted string.
     * @return
     * @throws UnsupportedKerasConfigurationException
     */
private String readAttributeAsJson(hdf5.Attribute attribute) throws UnsupportedKerasConfigurationException {
    hdf5.VarLenType vl = attribute.getVarLenType();
    int bufferSizeMult = 1;
    String s = null;
    /* TODO: find a less hacky way to do this.
         * Reading variable length strings (from attributes) is a giant
         * pain. There does not appear to be any way to determine the
         * length of the string in advance, so we use a hack: choose a
         * buffer size and read the config. If Jackson fails to parse
         * it, then we must not have read the entire config. Increase
         * buffer and repeat.
         */
    while (true) {
        byte[] attrBuffer = new byte[bufferSizeMult * 2000];
        BytePointer attrPointer = new BytePointer(attrBuffer);
        attribute.read(vl, attrPointer);
        attrPointer.get(attrBuffer);
        s = new String(attrBuffer);
        ObjectMapper mapper = new ObjectMapper();
        mapper.enable(DeserializationFeature.FAIL_ON_READING_DUP_TREE_KEY);
        try {
            mapper.readTree(s);
            break;
        } catch (IOException e) {
        }
        bufferSizeMult++;
        if (bufferSizeMult > 100) {
            throw new UnsupportedKerasConfigurationException("Could not read abnormally long HDF5 attribute");
        }
    }
    return s;
}

Example 15 with ObjectMapper

use of org.nd4j.shade.jackson.databind.ObjectMapper in project deeplearning4j by deeplearning4j.

the class KerasModel method parseJsonString.

/**
     * Convenience function for parsing JSON strings.
     *
     * @param json    String containing valid JSON
     * @return        Nested (key,value) map of arbitrary depth
     * @throws IOException
     */
public static Map<String, Object> parseJsonString(String json) throws IOException {
    ObjectMapper mapper = new ObjectMapper();
    TypeReference<HashMap<String, Object>> typeRef = new TypeReference<HashMap<String, Object>>() {
    };
    return mapper.readValue(json, typeRef);
}