Fix initialization check on de/serialization

src/main/java/weka/classifiers/functions/Dl4jMlpClassifier.java

@@ -239,6 +239,11 @@ public class Dl4jMlpClassifier extends RandomizableClassifier
    */
   protected IterationListener iterationListener = new EpochListener();
 
+  /**
+   * Flag indicating if initialization is finished.
+   */
+  protected boolean isInitializationFinished = false;
+
   /**
    * Default constructor
    */
@@ -350,7 +355,7 @@ public Capabilities getCapabilities() {
   private void writeObject(ObjectOutputStream oos) throws IOException {
     // figure out size of the written network
     CountingOutputStream cos = new CountingOutputStream(new NullOutputStream());
-    if (replaceMissingFilter != null) {
+    if (isInitializationFinished) {
       ModelSerializer.writeModel(model, cos, false);
     }
     modelSize = cos.getByteCount();
@@ -359,7 +364,7 @@ private void writeObject(ObjectOutputStream oos) throws IOException {
     oos.defaultWriteObject();
 
     // actually write the network
-    if (replaceMissingFilter != null) {
+    if (isInitializationFinished) {
       ModelSerializer.writeModel(model, oos, false);
     }
   }
@@ -377,7 +382,7 @@ private void readObject(ObjectInputStream ois) throws ClassNotFoundException, IO
       ois.defaultReadObject();
 
       // restore the network model
-      if (replaceMissingFilter != null) {
+      if (isInitializationFinished) {
         File tmpFile = File.createTempFile("restore", "multiLayer");
         tmpFile.deleteOnExit();
         BufferedOutputStream bos = new BufferedOutputStream(new FileOutputStream(tmpFile));
@@ -404,12 +409,22 @@ private void readObject(ObjectInputStream ois) throws ClassNotFoundException, IO
             .map(l -> Layer.create(l.conf().getLayer()))
             .toArray(Layer[]::new);
         System.out.println();
+      } else {
+        layers = new Layer[] {createOutputLayer()};
       }
     } finally {
       Thread.currentThread().setContextClassLoader(origLoader);
     }
   }
 
+  /**
+   * Generate the, for this model type, typical output layer.
+   * @return New OutputLayer object
+   */
+  protected Layer<? extends BaseOutputLayer> createOutputLayer(){
+    return new OutputLayer();
+  }
+
   /**
    * Get the log file
    *
@@ -729,6 +744,8 @@ public void initializeClassifier(Instances data) throws Exception {
       model.setListeners(getListener());
 
       numEpochsPerformed = 0;
+
+      isInitializationFinished = true;
     } finally {
       Thread.currentThread().setContextClassLoader(origLoader);
     }

src/main/java/weka/classifiers/functions/RnnSequenceClassifier.java

@@ -7,6 +7,7 @@
 import org.deeplearning4j.nn.conf.ComputationGraphConfiguration;
 import org.deeplearning4j.nn.conf.inputs.InputType;
 import org.deeplearning4j.nn.conf.layers.AbstractLSTM;
+import org.deeplearning4j.nn.conf.layers.BaseOutputLayer;
 import org.deeplearning4j.nn.conf.layers.EmbeddingLayer;
 import org.deeplearning4j.nn.conf.layers.GlobalPoolingLayer;
 import org.deeplearning4j.nn.conf.layers.RnnOutputLayer;
@@ -295,6 +296,14 @@ public void setZooModel(ZooModel zooModel) {
     // Do nothing
   }
 
+  /**
+   * Generate the, for this model type, typical output layer.
+   * @return New OutputLayer object
+   */
+  protected Layer<? extends BaseOutputLayer> createOutputLayer(){
+    return new weka.dl4j.layers.RnnOutputLayer();
+  }
+
   /**
    * Returns default capabilities of the classifier.
    *

src/test/java/weka/classifiers/functions/Dl4jMlpTest.java

@@ -302,13 +302,13 @@ public void testSerialization() throws Exception {
 
     File out = Paths.get(System.getProperty("java.io.tmpdir"), "out.object").toFile();
     ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream(out));
+    clf.initializeClassifier(dataMnist);
     oos.writeObject(clf);
 
     ObjectInputStream ois = new ObjectInputStream(new FileInputStream(out));
     Dl4jMlpClassifier clf2 = (Dl4jMlpClassifier) ois.readObject();
 
     clf2.setNumEpochs(1);
-    clf2.initializeClassifier(dataMnist);
     clf2.buildClassifier(dataMnist);
   }