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66 changes: 66 additions & 0 deletions
66
...nqs/psl/application/learning/weight/gradient/policygradient/PolicyGradientBinaryStep.java
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,66 @@ | ||
| /* | ||
| * This file is part of the PSL software. | ||
| * Copyright 2011-2015 University of Maryland | ||
| * Copyright 2013-2023 The Regents of the University of California | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
| package org.linqs.psl.application.learning.weight.gradient.policygradient; | ||
|
|
||
| import org.linqs.psl.database.AtomStore; | ||
| import org.linqs.psl.database.Database; | ||
| import org.linqs.psl.model.atom.ObservedAtom; | ||
| import org.linqs.psl.model.atom.RandomVariableAtom; | ||
| import org.linqs.psl.model.rule.Rule; | ||
| import org.linqs.psl.util.Logger; | ||
| import org.linqs.psl.util.MathUtils; | ||
|
|
||
| import java.util.List; | ||
| import java.util.Map; | ||
|
|
||
| /** | ||
| * Learns parameters for a model by minimizing the squared error loss function | ||
| * using the policy gradient learning framework. | ||
| */ | ||
| public class PolicyGradientBinaryStep extends PolicyGradient { | ||
| private static final Logger log = Logger.getLogger(PolicyGradientBinaryStep.class); | ||
|
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| public PolicyGradientBinaryStep(List<Rule> rules, Database trainTargetDatabase, Database trainTruthDatabase, | ||
| Database validationTargetDatabase, Database validationTruthDatabase, boolean runValidation) { | ||
| super(rules, trainTargetDatabase, trainTruthDatabase, validationTargetDatabase, validationTruthDatabase, runValidation); | ||
| } | ||
|
|
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| @Override | ||
| protected float computeSupervisedLoss() { | ||
| AtomStore atomStore = trainInferenceApplication.getTermStore().getAtomStore(); | ||
|
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| float supervisedLoss = 0.0f; | ||
| for (Map.Entry<RandomVariableAtom, ObservedAtom> entry : trainingMap.getLabelMap().entrySet()) { | ||
| RandomVariableAtom randomVariableAtom = entry.getKey(); | ||
| ObservedAtom observedAtom = entry.getValue(); | ||
|
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| int atomIndex = atomStore.getAtomIndex(randomVariableAtom); | ||
| if (atomIndex == -1) { | ||
| // This atom is not in the current batch. | ||
| continue; | ||
| } | ||
|
|
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| if (!MathUtils.equals(observedAtom.getValue(), atomStore.getAtom(atomIndex).getValue())) { | ||
| supervisedLoss = 1.0f; | ||
| break; | ||
| } | ||
| } | ||
|
|
||
| return supervisedLoss; | ||
| } | ||
| } |
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55
...psl/application/learning/weight/gradient/policygradient/PolicyGradientBinaryStepTest.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,55 @@ | ||
| /* | ||
| * This file is part of the PSL software. | ||
| * Copyright 2011-2015 University of Maryland | ||
| * Copyright 2013-2023 The Regents of the University of California | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
| package org.linqs.psl.application.learning.weight.gradient.policygradient; | ||
|
|
||
| import org.junit.Before; | ||
| import org.junit.Test; | ||
| import org.linqs.psl.application.inference.mpe.DualBCDInference; | ||
| import org.linqs.psl.application.learning.weight.WeightLearningApplication; | ||
| import org.linqs.psl.application.learning.weight.WeightLearningTest; | ||
| import org.linqs.psl.config.Options; | ||
|
|
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| public class PolicyGradientBinaryStepTest extends WeightLearningTest { | ||
| @Before | ||
| public void setup() { | ||
| super.setup(); | ||
|
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| Options.WLA_INFERENCE.set(DualBCDInference.class.getName()); | ||
| Options.WLA_GRADIENT_DESCENT_SYMBOLIC_LEARNING.set(false); | ||
| } | ||
|
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| @Override | ||
| protected WeightLearningApplication getBaseWLA() { | ||
| return new PolicyGradientBinaryStep(info.model.getRules(), trainTargetDatabase, trainTruthDatabase, | ||
| validationTargetDatabase, validationTruthDatabase, false); | ||
| } | ||
|
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| @Test | ||
| public void DualBCDFriendshipRankTest() { | ||
| Options.WLA_INFERENCE.set(DualBCDInference.class.getName()); | ||
|
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| super.friendshipRankTest(); | ||
| } | ||
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| @Test | ||
| public void DistributedDualBCDFriendshipRankTest() { | ||
| Options.WLA_INFERENCE.set(DualBCDInference.class.getName()); | ||
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| super.friendshipRankTest(); | ||
| } | ||
| } |