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panhongxpanhongx
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Add Scorer
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‎build.gradle

+1-1
Original file line numberDiff line numberDiff line change
@@ -43,5 +43,5 @@ allprojects {
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ext {
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pomGroupID = 'ai.improve'
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sdkVersion = '7.2.0'
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sdkVersion = '8.0.0'
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}

‎improveai-android/src/androidTest/java/ai/improve/TestScorer.java

+40
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@@ -0,0 +1,40 @@
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package ai.improve;
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import androidx.test.ext.junit.runners.AndroidJUnit4;
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import org.junit.Test;
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import org.junit.runner.RunWith;
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import java.io.IOException;
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import java.util.Arrays;
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import java.util.List;
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import ai.improve.log.IMPLog;
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@RunWith(AndroidJUnit4.class)
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public class TestScorer {
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public static final String Tag = "TestScorer";
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public static final String ModelUrl = "https://improveai-mindblown-mindful-prod-models.s3.amazonaws.com/models/latest/songs-2.0.xgb.gz";
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public static final String DummyV8ModelUrl = "file:///android_asset/dummy_v8.xgb";
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static {
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IMPLog.setLogLevel(IMPLog.LOG_LEVEL_ALL);
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}
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@Test
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public void testScore() throws IOException, InterruptedException {
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Scorer scorer = new Scorer(ModelUrl);
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List scores = scorer.score(Arrays.asList(0, 1, 2));
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IMPLog.d(Tag, "scores: " + scores);
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}
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@Test
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public void testLoad_v8_model() throws IOException, InterruptedException {
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Scorer scorer = new Scorer(DummyV8ModelUrl);
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List scores = scorer.score(Arrays.asList(0, 1, 2));
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IMPLog.d(Tag, "scores: " + scores);
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}
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}

‎improveai/src/main/java/ai/improve/Scorer.java

+80
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@@ -0,0 +1,80 @@
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package ai.improve;
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import java.io.IOException;
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import java.net.URL;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.concurrent.CountDownLatch;
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import ai.improve.downloader.ModelDownloader;
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import ai.improve.encoder.FeatureEncoder;
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import ai.improve.log.IMPLog;
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import ai.improve.xgbpredictor.ImprovePredictor;
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import biz.k11i.xgboost.util.FVec;
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public class Scorer {
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public static final String Tag = "Scorer";
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private CountDownLatch loadModelSignal = new CountDownLatch(1);
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private ImprovePredictor predictor;
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private FeatureEncoder featureEncoder;
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private boolean enableTieBreaker = true;
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public Scorer(String modelUrl) throws IOException, InterruptedException {
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loadModel(new URL(modelUrl));
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if(predictor == null) {
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throw new IOException("Failed to load model " + modelUrl);
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}
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}
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public <T> List<Double> score(List<?> items) {
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return score(items, null);
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}
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public <T> List<Double> score(List<?> items, T context) {
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if(items == null || items.size() <= 0) {
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throw new IllegalArgumentException("variants can't be null or empty");
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}
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List<Double> result = new ArrayList<>();
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List<FVec> encodedFeatures = featureEncoder.encodeFeatureVectors(items, context, Math.random());
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for (FVec fvec : encodedFeatures) {
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if(enableTieBreaker) {
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// add a very small random number to randomly break ties
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double smallNoise = Math.random() * Math.pow(2, -23);
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result.add((double) predictor.predictSingle(fvec) + smallNoise);
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} else {
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result.add((double) predictor.predictSingle(fvec));
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}
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}
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return result;
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}
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private synchronized void setModel(ImprovePredictor predictor) {
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this.predictor = predictor;
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featureEncoder = new FeatureEncoder(predictor.getModelMetadata().getModelFeatureNames(),
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predictor.getModelMetadata().getStringTables(),
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predictor.getModelMetadata().getModelSeed());
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}
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private void loadModel(URL modelUrl) throws InterruptedException {
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ModelDownloader.download(modelUrl, (predictor, e) -> {
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if(e != null) {
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IMPLog.e(Tag, "Failed to load model, " + e.getMessage());
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loadModelSignal.countDown();
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return;
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}
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setModel(predictor);
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loadModelSignal.countDown();
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});
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loadModelSignal.await();
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}
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}

‎improveai/src/main/java/ai/improve/encoder/FeatureEncoder.java

+9
Original file line numberDiff line numberDiff line change
@@ -113,7 +113,16 @@ public void encodeFeatureVector(Object item, Object context, double[] into, doub
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if (context != null) {
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encodeContext(context, into, noiseShiftAndScale[0], noiseShiftAndScale[1]);
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}
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}
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public List<FVec> encodeFeatureVectors(List<?> items, Object context, double noise) {
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List<FVec> result = new ArrayList<>();
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for(int i = 0; i < items.size(); ++i) {
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double[] fvalues = new double[this.featureIndexes.size()];
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encodeFeatureVector(items.get(i), context, fvalues, noise);
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result.add(FVec.Transformer.fromArray(fvalues, false));
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}
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return result;
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}
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/**

‎improveai/src/main/java/ai/improve/xgbpredictor/ModelMetadata.java

+25-4
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@@ -2,11 +2,15 @@
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import ai.improve.constants.BuildProperties;
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import biz.k11i.xgboost.util.ModelReader;
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import com.google.gson.Gson;
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import com.google.gson.JsonArray;
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import com.google.gson.JsonObject;
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import com.google.gson.JsonParser;
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import com.google.gson.reflect.TypeToken;
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import java.io.IOException;
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import java.lang.reflect.Type;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
@@ -19,6 +23,14 @@ public class ModelMetadata {
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public static final String IMPROVE_VERSION_KEY = "ai.improve.version";
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public static final String IMPROVE_SEED_KEY = "ai.improve.seed";
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public static final String IMPROVE_MODEL_NAME_KEY = "ai.improve.model";
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public static final String IMPROVE_FEAtURES_KEY = "ai.improve.features";
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public static final String IMPROVE_STRING_TABLES_KEY = "ai.improve.string_tables";
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private Map<String, String> storage = new HashMap<>();
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private String modelName;
@@ -27,6 +39,8 @@ public class ModelMetadata {
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private List<String> modelFeatureNames;
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private Map<String, List<Long>> stringTables;
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public ModelMetadata(ModelReader r) throws IOException {
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long num_attrs = r.readLong();
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for (long i = 0; i < num_attrs; ++i) {
@@ -56,6 +70,10 @@ public List<String> getModelFeatureNames() {
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return modelFeatureNames;
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}
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public Map<String, List<Long>> getStringTables() {
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return stringTables;
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}
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public String getValue(String key) {
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return storage.get(key);
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}
@@ -66,22 +84,25 @@ public String getUserDefinedMetadata() {
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private void parseMetadata(String value) throws IOException {
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try {
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JsonObject root = JsonParser.parseString(value).getAsJsonObject().getAsJsonObject("json");
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JsonObject root = JsonParser.parseString(value).getAsJsonObject();
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if(root.has(IMPROVE_VERSION_KEY)) {
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String modelVersion = root.get(IMPROVE_VERSION_KEY).getAsString();
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if(!canParseModel(modelVersion, BuildProperties.getSDKVersion())) {
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throw new IOException("Major version don't match. ImproveAI SDK version(" + BuildProperties.getSDKVersion()+") " +
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"can't load the model of version("+ modelVersion + ").");
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}
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}
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modelName = root.get("model_name").getAsString();
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modelSeed = root.get("model_seed").getAsLong();
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modelName = root.get(IMPROVE_MODEL_NAME_KEY).getAsString();
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modelSeed = root.get(IMPROVE_SEED_KEY).getAsLong();
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JsonArray featuresArray = root.get("feature_names").getAsJsonArray();
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JsonArray featuresArray = root.get(IMPROVE_FEAtURES_KEY).getAsJsonArray();
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modelFeatureNames = new ArrayList<>(featuresArray.size());
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for (int i = 0; i < featuresArray.size(); ++i) {
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modelFeatureNames.add(featuresArray.get(i).getAsString());
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}
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Type type = new TypeToken<Map<String, List<Long>>>(){}.getType();
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stringTables = new Gson().fromJson(root.get(IMPROVE_STRING_TABLES_KEY), type);
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} catch (RuntimeException e) {
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throw new IOException("Failed to parse the model metadata. Looks like the model being loaded is invalid.");
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}

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