jmazanec15 commented on code in PR #12582: URL: https://github.com/apache/lucene/pull/12582#discussion_r1362956122
########## lucene/core/src/java/org/apache/lucene/util/ScalarQuantizer.java: ########## @@ -0,0 +1,317 @@ +/* + * 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.util; + +import static org.apache.lucene.search.DocIdSetIterator.NO_MORE_DOCS; + +import java.io.IOException; +import java.util.Arrays; +import java.util.Random; +import java.util.stream.IntStream; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.VectorSimilarityFunction; + +/** + * Will scalar quantize float vectors into `int8` byte values. This is a lossy transformation. + * Scalar quantization works by first calculating the quantiles of the float vector values. The + * quantiles are calculated using the configured quantile/confidence interval. The [minQuantile, + * maxQuantile] are then used to scale the values into the range [0, 127] and bucketed into the + * nearest byte values. + * + * <h2>How Scalar Quantization Works</h2> + * + * <p>The basic mathematical equations behind this are fairly straight forward. Given a float vector + * `v` and a quantile `q` we can calculate the quantiles of the vector values [minQuantile, + * maxQuantile]. + * + * <pre class="prettyprint"> + * byte = (float - minQuantile) * 127/(maxQuantile - minQuantile) + * float = (maxQuantile - minQuantile)/127 * byte + minQuantile + * </pre> + * + * <p>This then means to multiply two float values together (e.g. dot_product) we can do the + * following: + * + * <pre class="prettyprint"> + * float1 * float2 ~= (byte1 * (maxQuantile - minQuantile)/127 + minQuantile) * (byte2 * (maxQuantile - minQuantile)/127 + minQuantile) + * float1 * float2 ~= (byte1 * byte2 * (maxQuantile - minQuantile)^2)/(127^2) + (byte1 * minQuantile * (maxQuantile - minQuantile)/127) + (byte2 * minQuantile * (maxQuantile - minQuantile)/127) + minQuantile^2 + * let alpha = (maxQuantile - minQuantile)/127 + * float1 * float2 ~= (byte1 * byte2 * alpha^2) + (byte1 * minQuantile * alpha) + (byte2 * minQuantile * alpha) + minQuantile^2 + * </pre> + * + * <p>The expansion for square distance is much simpler: + * + * <pre class="prettyprint"> + * square_distance = (float1 - float2)^2 + * (float1 - float2)^2 ~= (byte1 * alpha + minQuantile - byte2 * alpha - minQuantile)^2 + * = (alpha*byte1 + minQuantile)^2 + (alpha*byte2 + minQuantile)^2 - 2*(alpha*byte1 + minQuantile)(alpha*byte2 + minQuantile) + * this can be simplified to: + * = alpha^2 (byte1 - byte2)^2 + * </pre> + */ +public class ScalarQuantizer { + + public static final int SCALAR_QUANTIZATION_SAMPLE_SIZE = 25_000; Review Comment: Out of curiousity, why was 25K chose? Seems it will be about 12.5MB in memory per segment for 128-dimensional vectors which seems reasonable, but Im curious if it could be lower. ########## lucene/core/src/java/org/apache/lucene/util/ScalarQuantizer.java: ########## @@ -0,0 +1,316 @@ +/* + * 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.util; + +import static org.apache.lucene.search.DocIdSetIterator.NO_MORE_DOCS; + +import java.io.IOException; +import java.util.Arrays; +import java.util.Random; +import java.util.stream.IntStream; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.VectorSimilarityFunction; + +/** + * Will scalar quantize float vectors into `int8` byte values. This is a lossy transformation. + * Scalar quantization works by first calculating the quantiles of the float vector values. The + * quantiles are calculated using the configured quantile/confidence interval. The [minQuantile, + * maxQuantile] are then used to scale the values into the range [0, 127] and bucketed into the + * nearest byte values. + * + * <h2>How Scalar Quantization Works</h2> Review Comment: I see. Looked at `getUpperAndLowerQuantile` closer and that makes sense. ########## lucene/core/src/java/org/apache/lucene/util/ScalarQuantizer.java: ########## @@ -0,0 +1,267 @@ +/* + * 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.util; + +import static org.apache.lucene.search.DocIdSetIterator.NO_MORE_DOCS; + +import java.io.IOException; +import java.util.Arrays; +import java.util.Random; +import java.util.stream.IntStream; +import org.apache.lucene.index.FloatVectorValues; +import org.apache.lucene.index.VectorSimilarityFunction; + +/** Will scalar quantize float vectors into `int8` byte values */ +public class ScalarQuantizer { + + public static final int SCALAR_QUANTIZATION_SAMPLE_SIZE = 25_000; + + private final float alpha; + private final float scale; + private final float minQuantile, maxQuantile, configuredQuantile; + + /** + * @param minQuantile the lower quantile of the distribution + * @param maxQuantile the upper quantile of the distribution + * @param configuredQuantile The configured quantile/confidence interval used to calculate the + * quantiles. + */ + public ScalarQuantizer(float minQuantile, float maxQuantile, float configuredQuantile) { + assert maxQuantile >= maxQuantile; + this.minQuantile = minQuantile; + this.maxQuantile = maxQuantile; + this.scale = 127f / (maxQuantile - minQuantile); + this.alpha = (maxQuantile - minQuantile) / 127f; + this.configuredQuantile = configuredQuantile; + } + + /** + * Quantize a float vector into a byte vector + * + * @param src the source vector + * @param dest the destination vector + * @param similarityFunction the similarity function used to calculate the quantile + * @return the corrective offset that needs to be applied to the score + */ + public float quantize(float[] src, byte[] dest, VectorSimilarityFunction similarityFunction) { + assert src.length == dest.length; + float correctiveOffset = 0f; + for (int i = 0; i < src.length; i++) { + float v = src[i]; + float dx = Math.max(minQuantile, Math.min(maxQuantile, src[i])) - minQuantile; + float dxs = scale * dx; + float dxq = Math.round(dxs) * alpha; + correctiveOffset += minQuantile * (v - minQuantile / 2.0F) + (dx - dxq) * dxq; + dest[i] = (byte) Math.round(dxs); + } + if (similarityFunction.equals(VectorSimilarityFunction.EUCLIDEAN)) { + return 0; + } + return correctiveOffset; + } Review Comment: I think I am a little bit confused around the corrective offset - digging into it a little bit more. -- This is an automated message from the Apache Git Service. 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