ChrisHegarty commented on code in PR #13339: URL: https://github.com/apache/lucene/pull/13339#discussion_r1604777876
########## lucene/core/src/test/org/apache/lucene/internal/vectorization/TestVectorScorer.java: ########## @@ -0,0 +1,324 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You 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.apache.lucene.internal.vectorization; + +import static org.apache.lucene.index.VectorSimilarityFunction.COSINE; +import static org.apache.lucene.index.VectorSimilarityFunction.DOT_PRODUCT; +import static org.apache.lucene.index.VectorSimilarityFunction.EUCLIDEAN; +import static org.apache.lucene.index.VectorSimilarityFunction.MAXIMUM_INNER_PRODUCT; + +import com.carrotsearch.randomizedtesting.generators.RandomNumbers; +import java.io.ByteArrayOutputStream; +import java.io.IOException; +import java.util.Arrays; +import java.util.List; +import java.util.Objects; +import java.util.Random; +import java.util.function.Function; +import org.apache.lucene.codecs.hnsw.DefaultFlatVectorScorer; +import org.apache.lucene.codecs.hnsw.FlatVectorsScorer; +import org.apache.lucene.codecs.lucene95.OffHeapByteVectorValues; +import org.apache.lucene.index.VectorSimilarityFunction; +import org.apache.lucene.store.Directory; +import org.apache.lucene.store.IOContext; +import org.apache.lucene.store.IndexInput; +import org.apache.lucene.store.IndexOutput; +import org.apache.lucene.store.MMapDirectory; +import org.apache.lucene.tests.util.LuceneTestCase; +import org.apache.lucene.util.hnsw.RandomAccessVectorValues; +import org.junit.BeforeClass; + +public class TestVectorScorer extends LuceneTestCase { + + private static final double DELTA = 1e-5; + + static final FlatVectorsScorer DEFAULT_SCORER = new DefaultFlatVectorScorer(); + static final FlatVectorsScorer MEMSEG_SCORER = + VectorizationProvider.lookup(true).newFlatVectorScorer(); + + @BeforeClass + public static void beforeClass() throws Exception { + assumeTrue( + "Test only works when the Memory segment scorer is present.", + MEMSEG_SCORER.getClass() != DEFAULT_SCORER.getClass()); + } + + public void testSimpleScorer() throws IOException { + testSimpleScorer(MMapDirectory.DEFAULT_MAX_CHUNK_SIZE); + } + + public void testSimpleScorerSmallChunkSize() throws IOException { + long maxChunkSize = random().nextLong(4, 16); + testSimpleScorer(maxChunkSize); + } + + public void testSimpleScorerMedChunkSize() throws IOException { + // a chunk size where in some vectors will be copied on-heap, while others remain off-heap + testSimpleScorer(64); + } + + void testSimpleScorer(long maxChunkSize) throws IOException { + try (Directory dir = new MMapDirectory(createTempDir("testSimpleScorer"), maxChunkSize)) { + for (int dims : List.of(31, 32, 33)) { + // dimensions that, in some scenarios, cross the mmap chunk sizes + byte[][] vectors = new byte[2][dims]; + String fileName = "bar-" + dims; + try (IndexOutput out = dir.createOutput(fileName, IOContext.DEFAULT)) { + for (int i = 0; i < dims; i++) { + vectors[0][i] = (byte) i; + vectors[1][i] = (byte) (dims - i); + } + byte[] bytes = concat(vectors[0], vectors[1]); + out.writeBytes(bytes, 0, bytes.length); + } + try (IndexInput in = dir.openInput(fileName, IOContext.DEFAULT)) { + for (var sim : List.of(COSINE, EUCLIDEAN, DOT_PRODUCT, MAXIMUM_INNER_PRODUCT)) { + var vectorValues = vectorValues(dims, 2, in, sim); + for (var ords : List.of(List.of(0, 1), List.of(1, 0))) { + int idx0 = ords.get(0); + int idx1 = ords.get(1); + + // getRandomVectorScorerSupplier + var scorer1 = DEFAULT_SCORER.getRandomVectorScorerSupplier(sim, vectorValues); + float expected = scorer1.scorer(idx0).score(idx1); + var scorer2 = MEMSEG_SCORER.getRandomVectorScorerSupplier(sim, vectorValues); + assertEquals(scorer2.scorer(idx0).score(idx1), expected, DELTA); + + // getRandomVectorScorer + var scorer3 = DEFAULT_SCORER.getRandomVectorScorer(sim, vectorValues, vectors[idx0]); + assertEquals(scorer3.score(idx1), expected, DELTA); + var scorer4 = MEMSEG_SCORER.getRandomVectorScorer(sim, vectorValues, vectors[idx0]); + assertEquals(scorer4.score(idx1), expected, DELTA); + } + } + } + } + } + } + + public void testRandomScorer() throws IOException { + testRandomScorer(MMapDirectory.DEFAULT_MAX_CHUNK_SIZE, BYTE_ARRAY_RANDOM_FUNC); + } + + public void testRandomScorerMax() throws IOException { + testRandomScorer(MMapDirectory.DEFAULT_MAX_CHUNK_SIZE, BYTE_ARRAY_MAX_FUNC); + } + + public void testRandomScorerMin() throws IOException { + testRandomScorer(MMapDirectory.DEFAULT_MAX_CHUNK_SIZE, BYTE_ARRAY_MIN_FUNC); + } + + public void testRandomSmallChunkSize() throws IOException { + long maxChunkSize = randomLongBetween(32, 128); + testRandomScorer(maxChunkSize, BYTE_ARRAY_RANDOM_FUNC); + } + + void testRandomScorer(long maxChunkSize, Function<Integer, byte[]> byteArraySupplier) + throws IOException { + try (Directory dir = new MMapDirectory(createTempDir("testRandomScorer"), maxChunkSize)) { + final int dims = randomIntBetween(1, 4096); + final int size = randomIntBetween(2, 100); + final byte[][] vectors = new byte[size][]; + String fileName = "foo-" + dims; + try (IndexOutput out = dir.createOutput(fileName, IOContext.DEFAULT)) { + for (int i = 0; i < size; i++) { + var vec = byteArraySupplier.apply(dims); + out.writeBytes(vec, 0, vec.length); + vectors[i] = vec; + } + } + + try (IndexInput in = dir.openInput(fileName, IOContext.DEFAULT)) { + for (int times = 0; times < TIMES; times++) { + for (var sim : List.of(COSINE, EUCLIDEAN, DOT_PRODUCT, MAXIMUM_INNER_PRODUCT)) { + var vectorValues = vectorValues(dims, size, in, sim); + int idx0 = randomIntBetween(0, size - 1); + int idx1 = randomIntBetween(0, size - 1); // may be the same as idx0 - which is ok. + + // getRandomVectorScorerSupplier + var scorer1 = DEFAULT_SCORER.getRandomVectorScorerSupplier(sim, vectorValues); + float expected = scorer1.scorer(idx0).score(idx1); + var scorer2 = MEMSEG_SCORER.getRandomVectorScorerSupplier(sim, vectorValues); + assertEquals(scorer2.scorer(idx0).score(idx1), expected, DELTA); + + // getRandomVectorScorer + var scorer3 = DEFAULT_SCORER.getRandomVectorScorer(sim, vectorValues, vectors[idx0]); + assertEquals(scorer3.score(idx1), expected, DELTA); + var scorer4 = MEMSEG_SCORER.getRandomVectorScorer(sim, vectorValues, vectors[idx0]); + assertEquals(scorer4.score(idx1), expected, DELTA); + } + } + } + } + } + + public void testRandomSliceSmall() throws IOException { + testRandomSliceImpl(30, 64, 1, BYTE_ARRAY_RANDOM_FUNC); + } + + public void testRandomSlice() throws IOException { + int dims = randomIntBetween(1, 4096); + long maxChunkSize = randomLongBetween(32, 128); + int size = randomIntBetween(1, 129); + testRandomSliceImpl(dims, maxChunkSize, size, BYTE_ARRAY_RANDOM_FUNC); + } + + void testRandomSliceImpl( + int dims, long maxChunkSize, int initialPadding, Function<Integer, byte[]> byteArraySupplier) + throws IOException { + try (Directory dir = new MMapDirectory(createTempDir("testRandomSliceImpl"), maxChunkSize)) { + final int size = randomIntBetween(2, 100); + final byte[][] vectors = new byte[size][]; + String fileName = "baz-" + dims; + try (IndexOutput out = dir.createOutput(fileName, IOContext.DEFAULT)) { + byte[] ba = new byte[initialPadding]; + out.writeBytes(ba, 0, ba.length); + for (int i = 0; i < size; i++) { + var vec = byteArraySupplier.apply(dims); + out.writeBytes(vec, 0, vec.length); + vectors[i] = vec; + } + } + + try (var outter = dir.openInput(fileName, IOContext.DEFAULT); + var in = outter.slice("slice", initialPadding, outter.length() - initialPadding)) { + for (int times = 0; times < TIMES; times++) { + for (var sim : List.of(COSINE, EUCLIDEAN, DOT_PRODUCT, MAXIMUM_INNER_PRODUCT)) { + var vectorValues = vectorValues(dims, size, in, sim); + int idx0 = randomIntBetween(0, size - 1); + int idx1 = randomIntBetween(0, size - 1); // may be the same as idx0 - which is ok. + + // getRandomVectorScorerSupplier + var scorer1 = DEFAULT_SCORER.getRandomVectorScorerSupplier(sim, vectorValues); + float expected = scorer1.scorer(idx0).score(idx1); + var scorer2 = MEMSEG_SCORER.getRandomVectorScorerSupplier(sim, vectorValues); + assertEquals(scorer2.scorer(idx0).score(idx1), expected, DELTA); + + // getRandomVectorScorer + var scorer3 = DEFAULT_SCORER.getRandomVectorScorer(sim, vectorValues, vectors[idx0]); + assertEquals(scorer3.score(idx1), expected, DELTA); + var scorer4 = MEMSEG_SCORER.getRandomVectorScorer(sim, vectorValues, vectors[idx0]); + assertEquals(scorer4.score(idx1), expected, DELTA); + } + } + } + } + } + + // Tests with a large amount of data (> 2GB), which ensures that data offsets do not overflow + @Nightly Review Comment: This test creates a big file, but it's currently the only way to test that the offset calculations are correctly handled without overflow (if implemented using int)! -- This is an automated message from the Apache Git Service. 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