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73 changes: 73 additions & 0 deletions
73
.../main/java/org/linqs/psl/application/learning/weight/gradient/LearningBatchGenerator.java
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| /* | ||
| * 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; | ||
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| import org.linqs.psl.application.inference.InferenceApplication; | ||
| import org.linqs.psl.reasoner.term.ReasonerTerm; | ||
| import org.linqs.psl.reasoner.term.SimpleTermStore; | ||
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| import java.util.ArrayList; | ||
| import java.util.Collections; | ||
| import java.util.List; | ||
|
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| /** | ||
| * A class for generating batches of data for learning. | ||
| * A batch in this case is a set of atoms and terms defining a subgraph of the complete factor graph. | ||
| */ | ||
| public abstract class LearningBatchGenerator { | ||
| protected SimpleTermStore<? extends ReasonerTerm> fullTermStore; | ||
| protected List<SimpleTermStore<? extends ReasonerTerm>> batchTermStores; | ||
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| protected InferenceApplication inferenceApplication; | ||
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| public LearningBatchGenerator(InferenceApplication inferenceApplication) { | ||
| assert inferenceApplication.getTermStore() instanceof SimpleTermStore; | ||
| this.inferenceApplication = inferenceApplication; | ||
| this.fullTermStore = (SimpleTermStore<? extends ReasonerTerm>)inferenceApplication.getTermStore(); | ||
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| batchTermStores = new ArrayList<SimpleTermStore<? extends ReasonerTerm>>(); | ||
| } | ||
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| public void shuffle() { | ||
| Collections.shuffle(batchTermStores); | ||
| } | ||
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| public int getNumBatches() { | ||
| return batchTermStores.size(); | ||
| } | ||
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| public List<SimpleTermStore<? extends ReasonerTerm>> getBatchTermStores() { | ||
| return batchTermStores; | ||
| } | ||
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| public SimpleTermStore<? extends ReasonerTerm> getBatchTermStore(int index) { | ||
| return batchTermStores.get(index); | ||
| } | ||
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| public abstract void generateBatches(); | ||
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| public void clear() { | ||
| for (SimpleTermStore<? extends ReasonerTerm> termStore : batchTermStores) { | ||
| termStore.getAtomStore().close(); | ||
| termStore.clear(); | ||
| } | ||
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| batchTermStores.clear(); | ||
| } | ||
| } |
120 changes: 120 additions & 0 deletions
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...ain/java/org/linqs/psl/application/learning/weight/gradient/RandomNodeBatchGenerator.java
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,120 @@ | ||
| /* | ||
| * 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; | ||
|
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| import org.linqs.psl.application.inference.InferenceApplication; | ||
| import org.linqs.psl.config.Options; | ||
| import org.linqs.psl.database.AtomStore; | ||
| import org.linqs.psl.model.atom.GroundAtom; | ||
| import org.linqs.psl.model.atom.RandomVariableAtom; | ||
| import org.linqs.psl.reasoner.term.ReasonerTerm; | ||
| import org.linqs.psl.reasoner.term.SimpleTermStore; | ||
|
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| import java.util.*; | ||
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| public class RandomNodeBatchGenerator extends LearningBatchGenerator { | ||
| private final int numBatches; | ||
| private final int batchSize; | ||
| private final int bfsDepth; | ||
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| public RandomNodeBatchGenerator(InferenceApplication inferenceApplication) { | ||
| super(inferenceApplication); | ||
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| numBatches = Options.RANDOM_NODE_BATCH_GENERATOR_NUM_BATCHES.getInt(); | ||
| batchSize = (int) Math.ceil(((float) fullTermStore.getAtomStore().getNumRVAtoms()) / numBatches); | ||
| bfsDepth = Options.RANDOM_NODE_BATCH_GENERATOR_BFS_DEPTH.getInt(); | ||
| } | ||
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| @Override | ||
| public void generateBatches() { | ||
| // Clear out any old batches. | ||
| clear(); | ||
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| // Randomly sample batchSize number of random variable atoms from the full atom store and create a new term store and atom store for each batch. | ||
| ArrayList<GroundAtom> allAtoms = new ArrayList<GroundAtom>(Arrays.asList(Arrays.copyOf(fullTermStore.getAtomStore().getAtoms(), fullTermStore.getAtomStore().size()))); | ||
| Collections.shuffle(allAtoms); | ||
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| for (int i = 0; i < numBatches; i++) { | ||
| AtomStore batchAtomStore = new AtomStore(); | ||
| SimpleTermStore<? extends ReasonerTerm> batchTermStore = (SimpleTermStore<? extends ReasonerTerm>)inferenceApplication.createTermStore(); | ||
| batchTermStore.setAtomStore(batchAtomStore); | ||
| batchTermStores.add(batchTermStore); | ||
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| HashSet<ReasonerTerm> visitedTerms = new HashSet<>(); | ||
| HashSet<GroundAtom> visitedAtoms = new HashSet<>(); | ||
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| // The last batch may be smaller than the rest. | ||
| while ((batchAtomStore.size() < batchSize) && !allAtoms.isEmpty()) { | ||
| GroundAtom originalAtom = allAtoms.remove(0); | ||
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| if (originalAtom.isFixed()) { | ||
| continue; | ||
| } | ||
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| // Make a copy of the atom so that the batch atom store can be modified without affecting the full atom store. | ||
| RandomVariableAtom newBatchRVAtom = (RandomVariableAtom)originalAtom.copy(); | ||
| newBatchRVAtom.clearTerms(); | ||
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| if (!visitedAtoms.contains(originalAtom)) { | ||
| batchAtomStore.addAtom(newBatchRVAtom); | ||
| } | ||
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| // Perform a bfs on the factor graph starting from the sampled atoms to obtain batch terms. | ||
| ArrayList<ReasonerTerm> bfsCurrentDepthQueue = new ArrayList<ReasonerTerm>(originalAtom.getTerms()); | ||
| for (int depth = 0; depth < bfsDepth; depth++) { | ||
| ArrayList<ReasonerTerm> bfsNextDepthQueue = new ArrayList<ReasonerTerm>(); | ||
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| for (ReasonerTerm term : bfsCurrentDepthQueue) { | ||
| if (visitedTerms.contains(term)) { | ||
| continue; | ||
| } | ||
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| visitedTerms.add(term); | ||
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| int[] originalAtomIndexes = term.getAtomIndexes(); | ||
| int[] newAtomIndexes = new int[term.getAtomIndexes().length]; | ||
| for (int j = 0 ; j < term.size(); j ++) { | ||
| int atomIndex = originalAtomIndexes[j]; | ||
| GroundAtom atom = fullTermStore.getAtomStore().getAtom(atomIndex); | ||
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| if (visitedAtoms.contains(atom)) { | ||
| newAtomIndexes[j] = batchAtomStore.getAtomIndex(atom); | ||
| continue; | ||
| } | ||
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| visitedAtoms.add(atom); | ||
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| GroundAtom newBatchAtom = atom.copy(); | ||
| newBatchAtom.clearTerms(); | ||
| batchAtomStore.addAtom(newBatchAtom); | ||
| newAtomIndexes[j] = batchAtomStore.getAtomIndex(atom); | ||
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| bfsNextDepthQueue.addAll(atom.getTerms()); | ||
| } | ||
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| ReasonerTerm newBatchTerm = term.copy(); | ||
| newBatchTerm.setAtomIndexes(newAtomIndexes); | ||
| batchTermStore.add(newBatchTerm); | ||
| } | ||
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| bfsCurrentDepthQueue = bfsNextDepthQueue; | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } |
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