Adds protobuf serialization for the various baseline predictors, clas…

…sifier chains, and viterbi (#277)

* Adding protobuf serialization to ViterbiModel and DummyClassifierModel.

* Adding protobuf serialization to DummyRegressionModel.

* Adding classifier chain and independent multi-label protobuf serialization.

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

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2015-2020, Oracle and/or its affiliates. All rights reserved.
+ * Copyright (c) 2015, 2022, 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.
@@ -16,26 +16,37 @@
 
 package org.tribuo.classification.baseline;
 
+import com.google.protobuf.Any;
+import com.google.protobuf.InvalidProtocolBufferException;
 import com.oracle.labs.mlrg.olcut.util.Pair;
+import com.sun.org.apache.xpath.internal.operations.Mod;
 import org.tribuo.Example;
 import org.tribuo.Excuse;
 import org.tribuo.ImmutableFeatureMap;
 import org.tribuo.ImmutableOutputInfo;
 import org.tribuo.Model;
+import org.tribuo.Output;
 import org.tribuo.Prediction;
 import org.tribuo.classification.ImmutableLabelInfo;
 import org.tribuo.classification.Label;
 import org.tribuo.classification.LabelFactory;
 import org.tribuo.classification.baseline.DummyClassifierTrainer.DummyType;
+import org.tribuo.classification.protos.DummyClassifierModelProto;
+import org.tribuo.impl.ModelDataCarrier;
+import org.tribuo.math.la.DenseSparseMatrix;
+import org.tribuo.math.la.Tensor;
+import org.tribuo.protos.core.ModelProto;
 import org.tribuo.provenance.ModelProvenance;
 import org.tribuo.util.Util;
 
+import java.util.Arrays;
 import java.util.Collections;
 import java.util.HashMap;
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
 import java.util.Random;
+import java.util.stream.Collectors;
 
 import static org.tribuo.Trainer.DEFAULT_SEED;
 
@@ -45,6 +56,11 @@
 public class DummyClassifierModel extends Model<Label> {
     private static final long serialVersionUID = 1L;
 
+    /**
+     * Protobuf serialization version.
+     */
+    public static final int CURRENT_VERSION = 0;
+
     private final DummyType dummyType;
 
     private final Label constantLabel;
@@ -82,6 +98,55 @@ public class DummyClassifierModel extends Model<Label> {
         this.rng = null;
     }
 
+    private DummyClassifierModel(String name, ModelProvenance provenance, ImmutableFeatureMap featureMap,
+                                 ImmutableOutputInfo<Label> outputInfo, DummyType type, Label constantLabel,
+                                 double[] cdf, long seed) {
+        super(name, provenance, featureMap, outputInfo, false);
+        this.dummyType = type;
+        this.constantLabel = constantLabel;
+        this.cdf = cdf;
+        this.seed = seed;
+        this.rng = new Random(seed);
+    }
+
+    /**
+     * Deserialization factory.
+     * @param version The serialized object version.
+     * @param className The class name.
+     * @param message The serialized data.
+     */
+    public static DummyClassifierModel deserializeFromProto(int version, String className, Any message) throws InvalidProtocolBufferException {
+        if (version < 0 || version > CURRENT_VERSION) {
+            throw new IllegalArgumentException("Unknown version " + version + ", this class supports at most version " + CURRENT_VERSION);
+        }
+        DummyClassifierModelProto proto = message.unpack(DummyClassifierModelProto.class);
+
+        ModelDataCarrier<?> carrier = ModelDataCarrier.deserialize(proto.getMetadata());
+        if (!carrier.outputDomain().getOutput(0).getClass().equals(Label.class)) {
+            throw new IllegalStateException("Invalid protobuf, output domain is not a label domain, found " + carrier.outputDomain().getClass());
+        }
+        @SuppressWarnings("unchecked") // guarded by getClass
+        ImmutableOutputInfo<Label> outputDomain = (ImmutableOutputInfo<Label>) carrier.outputDomain();
+
+        DummyType dummyType = DummyType.valueOf(proto.getDummyType());
+
+        Output<?> output = Output.deserialize(proto.getConstantLabel());
+        if (!(output instanceof Label)) {
+            throw new IllegalStateException("Invalid protobuf, expected a label, found " + output.getClass());
+        }
+        Label constantLabel = (Label) output;
+
+        double[] cdf = null;
+        if (proto.getCdfCount() > 0) {
+            cdf = Util.toPrimitiveDouble(proto.getCdfList());
+        }
+
+        long seed = proto.getSeed();
+
+        return new DummyClassifierModel(carrier.name(), carrier.provenance(), carrier.featureDomain(), outputDomain,
+            dummyType, constantLabel, cdf, seed);
+    }
+
     @Override
     public Prediction<Label> predict(Example<Label> example) {
         switch (dummyType) {
@@ -110,6 +175,27 @@ public Optional<Excuse<Label>> getExcuse(Example<Label> example) {
         return Optional.of(new Excuse<>(example,predict(example),getTopFeatures(1)));
     }
 
+    @Override
+    public ModelProto serialize() {
+        ModelDataCarrier<Label> carrier = createDataCarrier();
+
+        DummyClassifierModelProto.Builder modelBuilder = DummyClassifierModelProto.newBuilder();
+        modelBuilder.setMetadata(carrier.serialize());
+        modelBuilder.setDummyType(dummyType.name());
+        modelBuilder.setConstantLabel(constantLabel.serialize());
+        if (cdf != null) {
+            modelBuilder.addAllCdf(Arrays.stream(cdf).boxed().collect(Collectors.toList()));
+        }
+        modelBuilder.setSeed(seed);
+
+        ModelProto.Builder builder = ModelProto.newBuilder();
+        builder.setSerializedData(Any.pack(modelBuilder.build()));
+        builder.setClassName(DummyClassifierModel.class.getName());
+        builder.setVersion(CURRENT_VERSION);
+
+        return builder.build();
+    }
+
     @Override
     protected DummyClassifierModel copy(String newName, ModelProvenance newProvenance) {
         switch (dummyType) {