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Add protobuf serialization for LibSVM based models #272

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merged 2 commits into from
Sep 19, 2022
Merged

Add protobuf serialization for LibSVM based models #272

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efde781
Roughing out libsvm protos.
Craigacp Sep 8, 2022
72cb1e8
Finishing LibSVM serialization.
Craigacp Sep 9, 2022
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55 changes: 53 additions & 2 deletions AnomalyDetection/LibSVM/src/main/java/org/tribuo/anomaly/libsvm/LibSVMAnomalyModel.java
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Original file line number Diff line number Diff line change
@@ -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.
Expand All @@ -16,13 +16,20 @@

package org.tribuo.anomaly.libsvm;

import com.google.protobuf.Any;
import com.google.protobuf.InvalidProtocolBufferException;
import org.tribuo.Example;
import org.tribuo.ImmutableFeatureMap;
import org.tribuo.ImmutableOutputInfo;
import org.tribuo.Prediction;
import org.tribuo.anomaly.Event;
import org.tribuo.anomaly.libsvm.protos.LibSVMAnomalyModelProto;
import org.tribuo.common.libsvm.LibSVMModel;
import org.tribuo.common.libsvm.LibSVMTrainer;
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 libsvm.svm;
import libsvm.svm_model;
Expand All @@ -32,7 +39,7 @@
import java.util.List;

/**
* A anomaly detection model that uses an underlying libSVM model to make the
* An anomaly detection model that uses an underlying libSVM model to make the
* predictions.
* <p>
* See:
Expand All @@ -52,10 +59,39 @@
public class LibSVMAnomalyModel extends LibSVMModel<Event> {
private static final long serialVersionUID = 1L;

/**
* Protobuf serialization version.
*/
public static final int CURRENT_VERSION = 0;

LibSVMAnomalyModel(String name, ModelProvenance description, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<Event> labelIDMap, List<svm_model> models) {
super(name, description, featureIDMap, labelIDMap, models.get(0).param.probability == 1, models);
}

/**
* Deserialization factory.
* @param version The serialized object version.
* @param className The class name.
* @param message The serialized data.
*/
public static LibSVMAnomalyModel 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);
}
LibSVMAnomalyModelProto proto = message.unpack(LibSVMAnomalyModelProto.class);

ModelDataCarrier<?> carrier = ModelDataCarrier.deserialize(proto.getMetadata());
if (!carrier.outputDomain().getOutput(0).getClass().equals(Event.class)) {
throw new IllegalStateException("Invalid protobuf, output domain is not an anomaly detection domain, found " + carrier.outputDomain().getClass());
}
@SuppressWarnings("unchecked") // guarded by getClass
ImmutableOutputInfo<Event> outputDomain = (ImmutableOutputInfo<Event>) carrier.outputDomain();

svm_model model = deserializeModel(proto.getModel());

return new LibSVMAnomalyModel(carrier.name(),carrier.provenance(),carrier.featureDomain(),outputDomain,Collections.singletonList(model));
}

/**
* Returns the number of support vectors.
* @return The number of support vectors.
Expand Down Expand Up @@ -85,4 +121,19 @@ protected LibSVMAnomalyModel copy(String newName, ModelProvenance newProvenance)
return new LibSVMAnomalyModel(newName,newProvenance,featureIDMap,outputIDInfo, Collections.singletonList(LibSVMModel.copyModel(models.get(0))));
}

@Override
public ModelProto serialize() {
ModelDataCarrier<Event> carrier = createDataCarrier();

LibSVMAnomalyModelProto.Builder modelBuilder = LibSVMAnomalyModelProto.newBuilder();
modelBuilder.setMetadata(carrier.serialize());
modelBuilder.setModel(serializeModel(models.get(0)));

ModelProto.Builder builder = ModelProto.newBuilder();
builder.setSerializedData(Any.pack(modelBuilder.build()));
builder.setClassName(LibSVMAnomalyModel.class.getName());
builder.setVersion(CURRENT_VERSION);

return builder.build();
}
}
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