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August 3, 2022 15:43
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/* | |
* Anserini: A Lucene toolkit for reproducible information retrieval research | |
* | |
* 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 io.anserini.ann; | |
import java.io.File; | |
import java.io.FileWriter; | |
import java.io.IOException; | |
import java.nio.file.Files; | |
import java.nio.file.Path; | |
import java.util.List; | |
import java.util.Map; | |
import org.apache.lucene.document.Document; | |
import org.apache.lucene.index.DirectoryReader; | |
import org.apache.lucene.search.IndexSearcher; | |
import org.apache.lucene.search.KnnVectorQuery; | |
import org.apache.lucene.search.ScoreDoc; | |
import org.apache.lucene.search.TopDocs; | |
import org.apache.lucene.store.Directory; | |
import org.apache.lucene.store.FSDirectory; | |
import org.kohsuke.args4j.CmdLineException; | |
import org.kohsuke.args4j.CmdLineParser; | |
import org.kohsuke.args4j.Option; | |
import org.kohsuke.args4j.OptionHandlerFilter; | |
import org.kohsuke.args4j.ParserProperties; | |
import static io.anserini.ann.IndexVectorsHNSW.FIELD_VECTOR; | |
public class ApproximateNearestNeighborEvalHNSW { | |
public static final class Args { | |
@Option(name = "-input", metaVar = "[file]", required = true, usage = "vectors model") | |
public File input; | |
@Option(name = "-path", metaVar = "[path]", required = true, usage = "index path") | |
public Path path; | |
@Option(name = "-topics", metaVar = "[file]", required = true, usage = "path to TREC topics file") | |
public Path topicsPath; | |
@Option(name = "-topN", metaVar = "[int]", usage = "topN recall") | |
public int topN = 10; | |
@Option(name = "-depth", metaVar = "[int]", usage = "retrieval depth") | |
public int depth = 10; | |
@Option(name = "-samples", metaVar = "[int]", usage = "no. of samples") | |
public int samples = Integer.MAX_VALUE; | |
} | |
public static void main(String[] args) throws Exception { | |
ApproximateNearestNeighborEvalHNSW.Args indexArgs = new ApproximateNearestNeighborEvalHNSW.Args(); | |
CmdLineParser parser = new CmdLineParser(indexArgs, ParserProperties.defaults().withUsageWidth(90)); | |
try { | |
parser.parseArgument(args); | |
} catch (CmdLineException e) { | |
System.err.println(e.getMessage()); | |
parser.printUsage(System.err); | |
System.err.println("Example: " + ApproximateNearestNeighborEvalHNSW.class.getSimpleName() + | |
parser.printExample(OptionHandlerFilter.REQUIRED)); | |
return; | |
} | |
System.out.println(String.format("Loading model %s", indexArgs.input)); | |
Map<String, List<float[]>> queryVectors = IndexVectorsHNSW.readVectors(indexArgs.input); | |
Path indexDir = indexArgs.path; | |
if (!Files.exists(indexDir)) { | |
Files.createDirectories(indexDir); | |
} | |
System.out.println(String.format("Reading index at %s", indexArgs.path)); | |
Directory d = FSDirectory.open(indexDir); | |
DirectoryReader reader = DirectoryReader.open(d); | |
IndexSearcher searcher = new IndexSearcher(reader); | |
double time = 0d; | |
System.out.println("Evaluating at retrieval depth: " + indexArgs.depth); | |
int queryCount = 0; | |
FileWriter writer = new FileWriter("msmarco.hnsw.tsv"); | |
for (Map.Entry<String, List<float[]>> queryVectorEntry : queryVectors.entrySet()) { | |
try { | |
List<float[]> vectors = queryVectorEntry.getValue(); | |
for (float[] queryVector : vectors) { | |
KnnVectorQuery simQuery = new KnnVectorQuery(FIELD_VECTOR, queryVector, indexArgs.topN); | |
long start = System.currentTimeMillis(); | |
TopDocs topDocs = searcher.search(simQuery, indexArgs.depth); | |
time += System.currentTimeMillis() - start; | |
int rank = 0; | |
for (ScoreDoc sd : topDocs.scoreDocs) { | |
Document document = reader.document(sd.doc); | |
String wordValue = document.get(IndexVectorsHNSW.FIELD_ID); | |
writer.append(queryVectorEntry.getKey()).append("\t").append(wordValue).append("\t") | |
.append(String.valueOf(rank)).append("\n"); | |
rank++; | |
} | |
writer.flush(); | |
queryCount++; | |
} | |
} catch (IOException e) { | |
System.err.println("search for '" + queryVectorEntry.getKey() + "' failed " + e.getLocalizedMessage()); | |
} | |
if (queryCount >= indexArgs.samples) { | |
break; | |
} | |
} | |
time /= queryCount; | |
System.out.println(String.format("avg query time: %s ms", time)); | |
writer.flush(); | |
writer.close(); | |
reader.close(); | |
d.close(); | |
} | |
} |
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