Remove java.io.Serializable

AnomalyDetection/Core/src/main/java/org/tribuo/anomaly/AnomalyFactory.java

@@ -35,7 +35,6 @@
  * A factory for generating events.
  */
 public final class AnomalyFactory implements OutputFactory<Event> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * The unknown event. Used at inference time.

AnomalyDetection/Core/src/main/java/org/tribuo/anomaly/AnomalyInfo.java

@@ -36,7 +36,6 @@
  * The base class for tracking anomalous events.
  */
 public abstract class AnomalyInfo implements OutputInfo<Event>  {
-    private static final long serialVersionUID = 1L;
 
     private static final Set<Event> DOMAIN = makeDomain();
 

AnomalyDetection/Core/src/main/java/org/tribuo/anomaly/Event.java

@@ -33,7 +33,6 @@
  * do support training from anomalous and expected data.
  */
 public final class Event implements Output<Event> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * The default score of events.

AnomalyDetection/Core/src/main/java/org/tribuo/anomaly/ImmutableAnomalyInfo.java

@@ -37,7 +37,6 @@
  */
 @ProtoSerializableClass(serializedDataClass=AnomalyInfoProto.class, version=0)
 public final class ImmutableAnomalyInfo extends AnomalyInfo implements ImmutableOutputInfo<Event> {
-    private static final long serialVersionUID = 1L;
 
     private static final Logger logger = Logger.getLogger(ImmutableAnomalyInfo.class.getName());
 

AnomalyDetection/Core/src/main/java/org/tribuo/anomaly/MutableAnomalyInfo.java

@@ -35,7 +35,6 @@
  */
 @ProtoSerializableClass(serializedDataClass=AnomalyInfoProto.class, version=0)
 public final class MutableAnomalyInfo extends AnomalyInfo implements MutableOutputInfo<Event> {
-    private static final long serialVersionUID = 1L;
 
     MutableAnomalyInfo() {
         super();

AnomalyDetection/LibLinear/src/main/java/org/tribuo/anomaly/liblinear/LibLinearAnomalyModel.java

@@ -66,7 +66,6 @@
  * </pre>
  */
 public class LibLinearAnomalyModel extends LibLinearModel<Event> {
-    private static final long serialVersionUID = 3L;
 
     private static final Logger logger = Logger.getLogger(LibLinearAnomalyModel.class.getName());
 

AnomalyDetection/LibLinear/src/main/java/org/tribuo/anomaly/liblinear/LinearAnomalyType.java

@@ -23,20 +23,17 @@
 import org.tribuo.common.liblinear.LibLinearType;
 import de.bwaldvogel.liblinear.SolverType;
 
-import java.io.Serializable;
-
 /**
  * The carrier type for liblinear anomaly detection modes.
  * <p>
  * Supports: ONECLASS_SVM
  */
 public final class LinearAnomalyType implements LibLinearType<Event> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * The different model types available for classification.
      */
-    public enum LinearType implements Serializable {
+    public enum LinearType {
         /**
          * Linear one-class SVM
          */

AnomalyDetection/LibLinear/src/test/java/org/tribuo/anomaly/liblinear/LibLinearAnomalyTrainerTest.java

@@ -75,7 +75,6 @@ public void gaussianDataTest() {
         logger.finer(output);
 
         // Test serialization
-        Helpers.testModelSerialization(model,Event.class);
         Helpers.testModelProtoSerialization(model,Event.class,testData);
     }
 

AnomalyDetection/LibSVM/src/main/java/org/tribuo/anomaly/libsvm/LibSVMAnomalyModel.java

@@ -55,7 +55,6 @@
  * </pre>
  */
 public class LibSVMAnomalyModel extends LibSVMModel<Event> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * Protobuf serialization version.

AnomalyDetection/LibSVM/src/main/java/org/tribuo/anomaly/libsvm/SVMAnomalyType.java

@@ -28,7 +28,6 @@
  * Supports ONE_CLASS. Yes it's a single value enum.
  */
 public class SVMAnomalyType implements SVMType<Event> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * Valid SVM modes for anomaly detection.

AnomalyDetection/LibSVM/src/test/java/org/tribuo/anomaly/libsvm/LibSVMAnomalyTrainerTest.java

@@ -76,9 +76,6 @@ public void gaussianDataTest() {
         logger.finer(confusion);
         logger.finer(output);
 
-        // Test serialization
-        Helpers.testModelSerialization(model,Event.class);
-
         // Test protobuf serialization
         Helpers.testModelProtoSerialization(model, Event.class, pair.getB());
     }

Classification/Core/src/main/java/org/tribuo/classification/ImmutableLabelInfo.java

@@ -44,8 +44,6 @@
 public class ImmutableLabelInfo extends LabelInfo implements ImmutableOutputInfo<Label> {
     private static final Logger logger = Logger.getLogger(ImmutableLabelInfo.class.getName());
 
-    private static final long serialVersionUID = 1L;
-
     private final Map<Integer,String> idLabelMap;
 
     private final Map<String,Integer> labelIDMap;
@@ -303,10 +301,4 @@ public Pair<Integer, Label> next() {
             return new Pair<>(e.getKey(),new Label(e.getValue()));
         }
     }
-
-    private void readObject(java.io.ObjectInputStream in) throws IOException, ClassNotFoundException {
-        in.defaultReadObject();
-
-        domain = Collections.unmodifiableSet(new HashSet<>(labels.values()));
-    }
 }

Classification/Core/src/main/java/org/tribuo/classification/Label.java

@@ -37,7 +37,6 @@
  */
 @ProtoSerializableClass(serializedDataClass=LabelProto.class, version=0)
 public final class Label implements Classifiable<Label> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * The name of the unknown label (i.e., an unlabelled output).

Classification/Core/src/main/java/org/tribuo/classification/LabelFactory.java

@@ -38,7 +38,6 @@
  * Label factories have no state, and are all equal to each other.
  */
 public final class LabelFactory implements OutputFactory<Label> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * The singleton unknown label, used for unlablled examples.

Classification/Core/src/main/java/org/tribuo/classification/LabelInfo.java

@@ -36,7 +36,6 @@
  * The base class for information about multi-class classification Labels.
  */
 public abstract class LabelInfo implements OutputInfo<Label> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * The occurrence counts of each label.
@@ -176,11 +175,4 @@ public MutableOutputInfo<Label> generateMutableOutputInfo() {
     @Override
     public abstract LabelInfo copy();
 
-    private void readObject(java.io.ObjectInputStream in) throws IOException, ClassNotFoundException {
-        in.defaultReadObject();
-        labels = new HashMap<>();
-        for (Map.Entry<String,MutableLong> e : labelCounts.entrySet()) {
-            labels.put(e.getKey(),new Label(e.getKey()));
-        }
-    }
 }

Classification/Core/src/main/java/org/tribuo/classification/MutableLabelInfo.java

@@ -35,7 +35,6 @@
  */
 @ProtoSerializableClass(serializedDataClass=MutableLabelInfoProto.class, version=0)
 public class MutableLabelInfo extends LabelInfo implements MutableOutputInfo<Label> {
-    private static final long serialVersionUID = 1L;
 
     MutableLabelInfo() {
         super();

Classification/Core/src/main/java/org/tribuo/classification/baseline/DummyClassifierModel.java

@@ -51,7 +51,6 @@
  * A model which performs dummy classifications (e.g., constant output, uniform sampled labels, stratified sampled labels).
  */
 public class DummyClassifierModel extends Model<Label> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * Protobuf serialization version.

Classification/Core/src/main/java/org/tribuo/classification/ensemble/FullyWeightedVotingCombiner.java

@@ -44,7 +44,6 @@
  * which uses the most likely prediction for each ensemble member.
  */
 public final class FullyWeightedVotingCombiner implements EnsembleCombiner<Label> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * Protobuf serialization version.

Classification/Core/src/main/java/org/tribuo/classification/ensemble/VotingCombiner.java

@@ -44,7 +44,6 @@
  * which uses the full distribution of predictions for each ensemble member.
  */
 public final class VotingCombiner implements EnsembleCombiner<Label> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * Protobuf serialization version.

Classification/Core/src/main/java/org/tribuo/classification/sequence/ConfidencePredictingSequenceModel.java

@@ -24,7 +24,6 @@
 import org.tribuo.sequence.SequenceExample;
 import org.tribuo.sequence.SequenceModel;
 
-import java.io.Serializable;
 import java.util.ArrayList;
 import java.util.List;
 
@@ -37,7 +36,6 @@
  * in a SequenceExample.
  */
 public abstract class ConfidencePredictingSequenceModel extends SequenceModel<Label> {
-    private static final long serialVersionUID = 1L;
 
     /**
      * Constructs a ConfidencePredictingSequenceModel with the supplied parameters.
@@ -86,8 +84,7 @@ private static <SUB extends Subsequence> Double multiplyWeights(List<Prediction<
     /**
      * A range class used to define a subsequence of a SequenceExample.
      */
-    public static class Subsequence implements Serializable {
-        private static final long serialVersionUID = 1L;
+    public static class Subsequence {
         /**
          * The subsequence start index.
          */

Classification/Core/src/main/java/org/tribuo/classification/sequence/SeqTrainTest.java

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2015, 2022, Oracle and/or its affiliates. All rights reserved.
+ * Copyright (c) 2015, 2023, Oracle and/or its affiliates. All rights reserved.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -28,11 +28,7 @@
 import org.tribuo.sequence.SequenceTrainer;
 import org.tribuo.util.Util;
 
-import java.io.BufferedInputStream;
 import java.io.IOException;
-import java.io.ObjectInputStream;
-import java.io.ObjectOutputStream;
-import java.nio.file.Files;
 import java.nio.file.Path;
 import java.util.logging.Logger;
 
@@ -77,16 +73,6 @@ public String getOptionsDescription() {
          */
         @Option(charName = 't', longName = "trainer-name", usage = "Name of the trainer in the configuration file.")
         public SequenceTrainer<Label> trainer;
-        /**
-         * Load in the data in protobuf format.
-         */
-        @Option(charName = 'p', longName = "protobuf-format-dataset", usage = "Load the model from a protobuf. Optional")
-        public boolean protobufFormat;
-        /**
-         * Write the model out in protobuf format.
-         */
-        @Option(longName = "write-protobuf-model", usage = "Write the model out in protobuf format.")
-        public boolean writeProtobuf;
     }
 
     /**
@@ -120,32 +106,15 @@ public static void main(String[] args) throws ClassNotFoundException, IOExceptio
                 break;
             default:
                 if ((o.trainDataset != null) && (o.testDataset != null)) {
-                    if (o.protobufFormat) {
-                        logger.info("Loading protobuf format training data from " + o.trainDataset);
-                        SequenceDataset<?> tmpTrain = SequenceDataset.deserializeFromFile(o.trainDataset);
-                        train = SequenceDataset.castDataset(tmpTrain, Label.class);
-                        logger.info(String.format("Loaded %d training examples for %s", train.size(), train.getOutputs().toString()));
-                        logger.info("Found " + train.getFeatureIDMap().size() + " features");
-                        logger.info("Loading protobuf format testing data from " + o.testDataset);
-                        SequenceDataset<?> tmpTest = SequenceDataset.deserializeFromFile(o.testDataset);
-                        test = SequenceDataset.castDataset(tmpTest, Label.class);
-                        logger.info(String.format("Loaded %d testing examples", test.size()));
-                    } else {
-                        logger.info("Loading training data from " + o.trainDataset);
-                        try (ObjectInputStream ois = new ObjectInputStream(new BufferedInputStream(Files.newInputStream(o.trainDataset)));
-                             ObjectInputStream oits = new ObjectInputStream(new BufferedInputStream(Files.newInputStream(o.testDataset)))) {
-                            @SuppressWarnings("unchecked") // deserialising a generic dataset.
-                            SequenceDataset<Label> tmpTrain = (SequenceDataset<Label>) ois.readObject();
-                            train = tmpTrain;
-                            logger.info(String.format("Loaded %d training examples for %s", train.size(), train.getOutputs().toString()));
-                            logger.info("Found " + train.getFeatureIDMap().size() + " features");
-                            logger.info("Loading testing data from " + o.testDataset);
-                            @SuppressWarnings("unchecked") // deserialising a generic dataset.
-                            SequenceDataset<Label> tmpTest = (SequenceDataset<Label>) oits.readObject();
-                            test = tmpTest;
-                            logger.info(String.format("Loaded %d testing examples", test.size()));
-                        }
-                    }
+                    logger.info("Loading training data from " + o.trainDataset);
+                    SequenceDataset<?> tmpTrain = SequenceDataset.deserializeFromFile(o.trainDataset);
+                    train = SequenceDataset.castDataset(tmpTrain, Label.class);
+                    logger.info(String.format("Loaded %d training examples for %s", train.size(), train.getOutputs().toString()));
+                    logger.info("Found " + train.getFeatureIDMap().size() + " features");
+                    logger.info("Loading testing data from " + o.testDataset);
+                    SequenceDataset<?> tmpTest = SequenceDataset.deserializeFromFile(o.testDataset);
+                    test = SequenceDataset.castDataset(tmpTest, Label.class);
+                    logger.info(String.format("Loaded %d testing examples", test.size()));
                 } else {
                     logger.warning("Unknown dataset " + o.datasetName);
                     logger.info(cm.usage());
@@ -169,13 +138,7 @@ public static void main(String[] args) throws ClassNotFoundException, IOExceptio
         System.out.println(evaluation.getConfusionMatrix().toString());
 
         if (o.outputPath != null) {
-            if (o.writeProtobuf) {
-                model.serializeToFile(o.outputPath);
-            } else {
-                try (ObjectOutputStream oos = new ObjectOutputStream(Files.newOutputStream(o.outputPath))) {
-                    oos.writeObject(model);
-                }
-            }
+            model.serializeToFile(o.outputPath);
             logger.info("Serialized model to file: " + o.outputPath);
         }
     }

Classification/Core/src/main/java/org/tribuo/classification/sequence/viterbi/DefaultFeatureExtractor.java

@@ -41,8 +41,6 @@
 @ProtoSerializableClass(serializedDataClass = DefaultFeatureExtractorProto.class, version = DefaultFeatureExtractor.CURRENT_VERSION)
 public class DefaultFeatureExtractor implements LabelFeatureExtractor {
 
-    private static final long serialVersionUID = 1L;
-
     /**
      * Protobuf serialization version.
      */

Classification/Core/src/main/java/org/tribuo/classification/sequence/viterbi/LabelFeatureExtractor.java

@@ -25,13 +25,12 @@
 import org.tribuo.protos.ProtoSerializable;
 import org.tribuo.protos.ProtoUtil;
 
-import java.io.Serializable;
 import java.util.List;
 
 /**
  * A class for featurising labels from previous steps in Viterbi.
  */
-public interface LabelFeatureExtractor extends Configurable, ProtoSerializable<LabelFeatureExtractorProto>, Provenancable<ConfiguredObjectProvenance>, Serializable {
+public interface LabelFeatureExtractor extends Configurable, ProtoSerializable<LabelFeatureExtractorProto>, Provenancable<ConfiguredObjectProvenance> {
 
     /**
      * Generates features based on the previously produced labels.

Classification/Core/src/main/java/org/tribuo/classification/sequence/viterbi/NoopFeatureExtractor.java

@@ -37,8 +37,6 @@
 @ProtoSerializableClass(version = NoopFeatureExtractor.CURRENT_VERSION)
 public class NoopFeatureExtractor implements LabelFeatureExtractor {
 
-    private static final long serialVersionUID = 1L;
-
     /**
      * Protobuf serialization version.
      */

Classification/Core/src/main/java/org/tribuo/classification/sequence/viterbi/ViterbiModel.java

@@ -47,8 +47,6 @@
  */
 public class ViterbiModel extends SequenceModel<Label> {
 
-    private static final long serialVersionUID = 1L;
-
     /**
      * Protobuf serialization version.
      */

Classification/Core/src/test/java/org/tribuo/classification/baseline/TestDummyClassifier.java

@@ -57,7 +57,6 @@ public static void testDummyClassifier(Pair<Dataset<Label>, Dataset<Label>> p, b
             Evaluator<Label, LabelEvaluation> evaluator = new LabelEvaluator();
             LabelEvaluation evaluation = evaluator.evaluate(m,p.getB());
             if (testModelSave) {
-                Helpers.testModelSerialization(m,Label.class);
                 Helpers.testModelProtoSerialization(m, Label.class, p.getB());
             }
         }

Classification/Core/src/test/java/org/tribuo/classification/ensemble/VotingCombinerTest.java

@@ -127,7 +127,7 @@ public void votingCombinerTest() {
         assertEquals(prediction.getOutput(),dishwasher);
         modelList.clear();
 
-        Helpers.testModelSerialization(ensemble,Label.class);
+        Helpers.testModelProtoSerialization(ensemble,Label.class);
     }
 
     @Test

Classification/DecisionTree/src/main/java/org/tribuo/classification/dtree/impl/ClassifierTrainingNode.java

@@ -49,7 +49,6 @@
  * the current impurity and a bunch of other statistics.
  */
 public class ClassifierTrainingNode extends AbstractTrainingNode<Label> {
-    private static final long serialVersionUID = 1L;
 
     private static final Logger logger = Logger.getLogger(ClassifierTrainingNode.class.getName());
 
@@ -432,8 +431,4 @@ private static ArrayList<TreeFeature> invertData(Dataset<Label> examples) {
         return data;
     }
 
-    private void writeObject(java.io.ObjectOutputStream stream)
-            throws IOException {
-        throw new NotSerializableException("ClassifierTrainingNode is a runtime class only, and should not be serialized.");
-    }
 }