mirror of https://github.com/apache/lucene.git
Fix default flat vector scorer supplier sharing backing array (#13355)
This commit fixes an issue in the default flat vector scorer supplier whereby subsequent scorers created by the supplier can affect previously created scorers. The issue is that we're sharing the backing array from the vector values, and overwriting it in subsequent scorers. We just need to use the ordinal to protect the scorer instance from mutation.
This commit is contained in:
Chris Hegarty
GitHub
parent
701c75a412
commit
25f1efd8eb
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@ -100,8 +100,13 @@ public class DefaultFlatVectorScorer implements FlatVectorsScorer {
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}
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@Override
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public RandomVectorScorer scorer(int ord) throws IOException {
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return new ByteVectorScorer(vectors2, vectors1.vectorValue(ord), similarityFunction);
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public RandomVectorScorer scorer(int ord) {
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return new RandomVectorScorer.AbstractRandomVectorScorer(vectors) {
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@Override
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public float score(int node) throws IOException {
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return similarityFunction.compare(vectors1.vectorValue(ord), vectors2.vectorValue(node));
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}
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};
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}
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@Override
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@ -127,8 +132,13 @@ public class DefaultFlatVectorScorer implements FlatVectorsScorer {
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}
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@Override
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public RandomVectorScorer scorer(int ord) throws IOException {
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return new FloatVectorScorer(vectors2, vectors1.vectorValue(ord), similarityFunction);
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public RandomVectorScorer scorer(int ord) {
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return new RandomVectorScorer.AbstractRandomVectorScorer(vectors) {
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@Override
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public float score(int node) throws IOException {
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return similarityFunction.compare(vectors1.vectorValue(ord), vectors2.vectorValue(node));
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}
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};
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}
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@Override
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@ -0,0 +1,216 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.lucene.codecs.hnsw;
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import static org.apache.lucene.index.VectorSimilarityFunction.COSINE;
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import static org.apache.lucene.index.VectorSimilarityFunction.DOT_PRODUCT;
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import static org.apache.lucene.index.VectorSimilarityFunction.EUCLIDEAN;
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import static org.apache.lucene.index.VectorSimilarityFunction.MAXIMUM_INNER_PRODUCT;
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import static org.hamcrest.Matchers.equalTo;
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import com.carrotsearch.randomizedtesting.annotations.ParametersFactory;
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import java.io.ByteArrayOutputStream;
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import java.io.IOException;
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import java.nio.ByteBuffer;
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import java.nio.ByteOrder;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.concurrent.atomic.AtomicInteger;
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import org.apache.lucene.codecs.lucene95.OffHeapByteVectorValues;
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import org.apache.lucene.codecs.lucene95.OffHeapFloatVectorValues;
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import org.apache.lucene.codecs.lucene99.Lucene99ScalarQuantizedVectorScorer;
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import org.apache.lucene.index.VectorSimilarityFunction;
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import org.apache.lucene.store.Directory;
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import org.apache.lucene.store.IOContext;
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import org.apache.lucene.store.IndexInput;
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import org.apache.lucene.store.IndexOutput;
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import org.apache.lucene.store.MMapDirectory;
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import org.apache.lucene.tests.util.LuceneTestCase;
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import org.apache.lucene.util.hnsw.RandomAccessVectorValues;
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import org.hamcrest.Matcher;
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import org.hamcrest.MatcherAssert;
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public class TestFlatVectorScorer extends LuceneTestCase {
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static volatile AtomicInteger count = new AtomicInteger();
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final FlatVectorsScorer flatVectorsScorer;
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final ThrowingSupplier<Directory> newDirectory;
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public TestFlatVectorScorer(
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FlatVectorsScorer flatVectorsScorer, ThrowingSupplier<Directory> newDirectory) {
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this.flatVectorsScorer = flatVectorsScorer;
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this.newDirectory = newDirectory;
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}
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@ParametersFactory
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public static Iterable<Object[]> parametersFactory() {
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var scorers =
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List.of(
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new DefaultFlatVectorScorer(),
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new Lucene99ScalarQuantizedVectorScorer(new DefaultFlatVectorScorer()));
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var dirs =
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List.<ThrowingSupplier<Directory>>of(
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TestFlatVectorScorer::newDirectory,
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() -> new MMapDirectory(createTempDir(count.getAndIncrement() + "-")));
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List<Object[]> objs = new ArrayList<>();
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for (var scorer : scorers) {
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for (var dir : dirs) {
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objs.add(new Object[] {scorer, dir});
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}
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}
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return objs;
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}
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// Tests that the creation of another scorer does not perturb previous scorers
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public void testMultipleByteScorers() throws IOException {
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byte[] vec0 = new byte[] {0, 0, 0, 0};
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byte[] vec1 = new byte[] {1, 1, 1, 1};
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byte[] vec2 = new byte[] {15, 15, 15, 15};
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String fileName = "testMultipleByteScorers";
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try (Directory dir = newDirectory.get()) {
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try (IndexOutput out = dir.createOutput(fileName, IOContext.DEFAULT)) {
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out.writeBytes(concat(vec0, vec1, vec2), 0, vec0.length * 3);
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}
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try (IndexInput in = dir.openInput(fileName, IOContext.DEFAULT)) {
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var vectorValues = byteVectorValues(4, 3, in, EUCLIDEAN);
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var ss = flatVectorsScorer.getRandomVectorScorerSupplier(EUCLIDEAN, vectorValues);
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var scorerAgainstOrd0 = ss.scorer(0);
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var firstScore = scorerAgainstOrd0.score(1);
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@SuppressWarnings("unused")
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var scorerAgainstOrd2 = ss.scorer(2);
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var scoreAgain = scorerAgainstOrd0.score(1);
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assertThat(scoreAgain, equalTo(firstScore));
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}
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}
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}
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// Tests that the creation of another scorer does not perturb previous scorers
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public void testMultipleFloatScorers() throws IOException {
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float[] vec0 = new float[] {0, 0, 0, 0};
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float[] vec1 = new float[] {1, 1, 1, 1};
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float[] vec2 = new float[] {15, 15, 15, 15};
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String fileName = "testMultipleFloatScorers";
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try (Directory dir = newDirectory.get()) {
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try (IndexOutput out = dir.createOutput(fileName, IOContext.DEFAULT)) {
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out.writeBytes(concat(vec0, vec1, vec2), 0, vec0.length * Float.BYTES * 3);
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}
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try (IndexInput in = dir.openInput(fileName, IOContext.DEFAULT)) {
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var vectorValues = floatVectorValues(4, 3, in, EUCLIDEAN);
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var ss = flatVectorsScorer.getRandomVectorScorerSupplier(EUCLIDEAN, vectorValues);
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var scorerAgainstOrd0 = ss.scorer(0);
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var firstScore = scorerAgainstOrd0.score(1);
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@SuppressWarnings("unused")
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var scorerAgainstOrd2 = ss.scorer(2);
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var scoreAgain = scorerAgainstOrd0.score(1);
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assertThat(scoreAgain, equalTo(firstScore));
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}
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}
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}
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public void testCheckByteDimensions() throws IOException {
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byte[] vec0 = new byte[4];
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String fileName = "testCheckByteDimensions";
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try (Directory dir = newDirectory.get()) {
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try (IndexOutput out = dir.createOutput(fileName, IOContext.DEFAULT)) {
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out.writeBytes(vec0, 0, vec0.length);
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}
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try (IndexInput in = dir.openInput(fileName, IOContext.DEFAULT)) {
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for (var sim : List.of(COSINE, DOT_PRODUCT, EUCLIDEAN, MAXIMUM_INNER_PRODUCT)) {
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var vectorValues = byteVectorValues(4, 1, in, sim);
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expectThrows(
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IllegalArgumentException.class,
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() -> flatVectorsScorer.getRandomVectorScorer(sim, vectorValues, new byte[5]));
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}
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}
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}
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}
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public void testCheckFloatDimensions() throws IOException {
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float[] vec0 = new float[4];
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String fileName = "testCheckFloatDimensions";
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try (Directory dir = newDirectory.get()) {
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try (IndexOutput out = dir.createOutput(fileName, IOContext.DEFAULT)) {
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out.writeBytes(concat(vec0), 0, vec0.length * Float.BYTES);
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}
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try (IndexInput in = dir.openInput(fileName, IOContext.DEFAULT)) {
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for (var sim : List.of(COSINE, DOT_PRODUCT, EUCLIDEAN, MAXIMUM_INNER_PRODUCT)) {
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var vectorValues = floatVectorValues(4, 1, in, sim);
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expectThrows(
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IllegalArgumentException.class,
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() -> flatVectorsScorer.getRandomVectorScorer(sim, vectorValues, new float[5]));
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}
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}
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}
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}
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RandomAccessVectorValues byteVectorValues(
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int dims, int size, IndexInput in, VectorSimilarityFunction sim) throws IOException {
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return new OffHeapByteVectorValues.DenseOffHeapVectorValues(
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dims, size, in.slice("byteValues", 0, in.length()), dims, flatVectorsScorer, sim);
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}
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RandomAccessVectorValues floatVectorValues(
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int dims, int size, IndexInput in, VectorSimilarityFunction sim) throws IOException {
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return new OffHeapFloatVectorValues.DenseOffHeapVectorValues(
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dims,
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size,
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in.slice("floatValues", 0, in.length()),
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dims * Float.BYTES,
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flatVectorsScorer,
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sim);
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}
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/** Concatenates float arrays as byte[]. */
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public static byte[] concat(float[]... arrays) throws IOException {
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var bb = ByteBuffer.allocate(4).order(ByteOrder.LITTLE_ENDIAN);
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try (ByteArrayOutputStream baos = new ByteArrayOutputStream()) {
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for (var fa : arrays) {
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for (var f : fa) {
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bb.putFloat(0, f);
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baos.write(bb.array());
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}
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}
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return baos.toByteArray();
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}
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}
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/** Concatenates byte arrays. */
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public static byte[] concat(byte[]... arrays) throws IOException {
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try (ByteArrayOutputStream baos = new ByteArrayOutputStream()) {
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for (var ba : arrays) {
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baos.write(ba);
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}
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return baos.toByteArray();
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}
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}
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public static <T> void assertThat(T actual, Matcher<? super T> matcher) {
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MatcherAssert.assertThat("", actual, matcher);
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}
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@FunctionalInterface
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public interface ThrowingSupplier<T> {
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T get() throws IOException;
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}
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}
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