[ML] enable logging for test failures (#60902)

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/inference/EnsembleInferenceModel.java

@@ -6,8 +6,11 @@
 
 package org.elasticsearch.xpack.core.ml.inference.trainedmodel.inference;
 
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
 import org.apache.lucene.util.RamUsageEstimator;
 import org.elasticsearch.common.Nullable;
+import org.elasticsearch.common.Strings;
 import org.elasticsearch.common.collect.Tuple;
 import org.elasticsearch.common.xcontent.ConstructingObjectParser;
 import org.elasticsearch.common.xcontent.XContentParser;
@@ -25,6 +28,7 @@ import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.Leniently
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.OutputAggregator;
 import org.elasticsearch.xpack.core.ml.utils.ExceptionsHelper;
 
+import java.util.Arrays;
 import java.util.Collections;
 import java.util.HashMap;
 import java.util.LinkedHashSet;
@@ -49,6 +53,7 @@ import static org.elasticsearch.xpack.core.ml.inference.trainedmodel.ensemble.En
 public class EnsembleInferenceModel implements InferenceModel {
 
     public static final long SHALLOW_SIZE = RamUsageEstimator.shallowSizeOfInstance(EnsembleInferenceModel.class);
+    private static final Logger LOGGER = LogManager.getLogger(EnsembleInferenceModel.class);
 
     @SuppressWarnings("unchecked")
     private static final ConstructingObjectParser<EnsembleInferenceModel, Void> PARSER = new ConstructingObjectParser<>(
@@ -136,6 +141,8 @@ public class EnsembleInferenceModel implements InferenceModel {
         if (preparedForInference == false) {
             throw ExceptionsHelper.serverError("model is not prepared for inference");
         }
+        LOGGER.debug("Inference called with feature names [{}]",
+            featureNames == null ? "<null>" : Strings.arrayToCommaDelimitedString(featureNames));
         assert featureNames != null && featureNames.length > 0;
         double[][] inferenceResults = new double[this.models.size()][];
         double[][] featureInfluence = new double[features.length][];
@@ -237,12 +244,14 @@ public class EnsembleInferenceModel implements InferenceModel {
 
     @Override
     public void rewriteFeatureIndices(Map<String, Integer> newFeatureIndexMapping) {
+        LOGGER.debug("rewriting features {}", newFeatureIndexMapping);
         if (preparedForInference) {
             return;
         }
         preparedForInference = true;
         if (newFeatureIndexMapping == null || newFeatureIndexMapping.isEmpty()) {
             Set<String> referencedFeatures = subModelFeatures();
+            LOGGER.debug("detected submodel feature names {}", referencedFeatures);
             int newFeatureIndex = 0;
             newFeatureIndexMapping = new HashMap<>();
             this.featureNames = new String[referencedFeatures.size()];
@@ -301,4 +310,16 @@ public class EnsembleInferenceModel implements InferenceModel {
         return classificationWeights;
     }
 
+    @Override
+    public String toString() {
+        return "EnsembleInferenceModel{" +
+            "featureNames=" + Arrays.toString(featureNames) +
+            ", models=" + models +
+            ", outputAggregator=" + outputAggregator +
+            ", targetType=" + targetType +
+            ", classificationLabels=" + classificationLabels +
+            ", classificationWeights=" + Arrays.toString(classificationWeights) +
+            ", preparedForInference=" + preparedForInference +
+            '}';
+    }
 }

x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/inference/TreeInferenceModel.java

@@ -6,6 +6,8 @@
 
 package org.elasticsearch.xpack.core.ml.inference.trainedmodel.inference;
 
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
 import org.apache.lucene.util.Accountable;
 import org.elasticsearch.common.Nullable;
 import org.elasticsearch.common.Numbers;
@@ -28,6 +30,7 @@ import org.elasticsearch.xpack.core.ml.inference.utils.Statistics;
 import org.elasticsearch.xpack.core.ml.job.config.Operator;
 import org.elasticsearch.xpack.core.ml.utils.ExceptionsHelper;
 
+import java.util.Arrays;
 import java.util.Collections;
 import java.util.List;
 import java.util.Map;
@@ -56,6 +59,7 @@ import static org.elasticsearch.xpack.core.ml.inference.trainedmodel.tree.TreeNo
 
 public class TreeInferenceModel implements InferenceModel {
 
+    private static final Logger LOGGER = LogManager.getLogger(TreeInferenceModel.class);
     public static final long SHALLOW_SIZE = shallowSizeOfInstance(TreeInferenceModel.class);
 
     @SuppressWarnings("unchecked")
@@ -304,6 +308,7 @@ public class TreeInferenceModel implements InferenceModel {
 
     @Override
     public void rewriteFeatureIndices(Map<String, Integer> newFeatureIndexMapping) {
+        LOGGER.debug("rewriting features {}", newFeatureIndexMapping);
         if (preparedForInference) {
             return;
         }
@@ -358,6 +363,20 @@ public class TreeInferenceModel implements InferenceModel {
         return nodes;
     }
 
+    @Override
+    public String toString() {
+        return "TreeInferenceModel{" +
+            "nodes=" + Arrays.toString(nodes) +
+            ", featureNames=" + Arrays.toString(featureNames) +
+            ", targetType=" + targetType +
+            ", classificationLabels=" + classificationLabels +
+            ", highOrderCategory=" + highOrderCategory +
+            ", maxDepth=" + maxDepth +
+            ", leafSize=" + leafSize +
+            ", preparedForInference=" + preparedForInference +
+            '}';
+    }
+
     private static int getDepth(Node[] nodes, int nodeIndex, int depth) {
         Node node = nodes[nodeIndex];
         if (node instanceof LeafNode) {
@@ -519,6 +538,19 @@ public class TreeInferenceModel implements InferenceModel {
         public long ramBytesUsed() {
             return SHALLOW_SIZE;
         }
+
+        @Override
+        public String toString() {
+            return "InnerNode{" +
+                "operator=" + operator +
+                ", threshold=" + threshold +
+                ", splitFeature=" + splitFeature +
+                ", defaultLeft=" + defaultLeft +
+                ", leftChild=" + leftChild +
+                ", rightChild=" + rightChild +
+                ", numberSamples=" + numberSamples +
+                '}';
+        }
     }
 
     public static class LeafNode extends Node {
@@ -544,5 +576,13 @@ public class TreeInferenceModel implements InferenceModel {
         public double[] getLeafValue() {
             return leafValue;
         }
+
+        @Override
+        public String toString() {
+            return "LeafNode{" +
+                "leafValue=" + Arrays.toString(leafValue) +
+                ", numberSamples=" + numberSamples +
+                '}';
+        }
     }
 }

x-pack/plugin/ml/qa/native-multi-node-tests/src/test/java/org/elasticsearch/xpack/ml/integration/ClassificationIT.java

@@ -18,6 +18,7 @@ import org.elasticsearch.action.index.IndexAction;
 import org.elasticsearch.action.index.IndexRequest;
 import org.elasticsearch.action.search.SearchResponse;
 import org.elasticsearch.action.support.WriteRequest;
+import org.elasticsearch.common.settings.Settings;
 import org.elasticsearch.common.unit.TimeValue;
 import org.elasticsearch.index.query.QueryBuilder;
 import org.elasticsearch.index.query.QueryBuilders;
@@ -36,6 +37,7 @@ import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.Multi
 import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.Precision;
 import org.elasticsearch.xpack.core.ml.dataframe.evaluation.classification.Recall;
 import org.junit.After;
+import org.junit.Before;
 
 import java.io.IOException;
 import java.util.ArrayList;
@@ -83,9 +85,25 @@ public class ClassificationIT extends MlNativeDataFrameAnalyticsIntegTestCase {
     private String destIndex;
     private boolean analysisUsesExistingDestIndex;
 
+    @Before
+    public void setupLogging() {
+        client().admin().cluster()
+            .prepareUpdateSettings()
+            .setTransientSettings(Settings.builder()
+                .put("logger.org.elasticsearch.xpack.ml.dataframe.inference", "DEBUG")
+                .put("logger.org.elasticsearch.xpack.core.ml.inference", "DEBUG"))
+            .get();
+    }
+
     @After
     public void cleanup() {
         cleanUp();
+        client().admin().cluster()
+            .prepareUpdateSettings()
+            .setTransientSettings(Settings.builder()
+                .putNull("logger.org.elasticsearch.xpack.ml.dataframe.inference")
+                .putNull("logger.org.elasticsearch.xpack.core.ml.inference"))
+            .get();
     }
 
     public void testSingleNumericFeatureAndMixedTrainingAndNonTrainingRows() throws Exception {

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/dataframe/inference/InferenceRunner.java

@@ -85,6 +85,7 @@ public class InferenceRunner {
             TestDocsIterator testDocsIterator = new TestDocsIterator(new OriginSettingClient(client, ClientHelper.ML_ORIGIN), config,
                 extractedFields);
             try (LocalModel localModel = localModelPlainActionFuture.actionGet()) {
+                LOGGER.debug("Loaded inference model [{}]", localModel);
                 inferTestDocs(localModel, testDocsIterator);
             }
         } catch (Exception e) {

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/inference/loadingservice/LocalModel.java

@@ -228,4 +228,22 @@ public class LocalModel implements Closeable {
     public void close() {
         release();
     }
+
+    @Override
+    public String toString() {
+        return "LocalModel{" +
+            "trainedModelDefinition=" + trainedModelDefinition +
+            ", modelId='" + modelId + '\'' +
+            ", fieldNames=" + fieldNames +
+            ", defaultFieldMap=" + defaultFieldMap +
+            ", statsAccumulator=" + statsAccumulator +
+            ", trainedModelStatsService=" + trainedModelStatsService +
+            ", persistenceQuotient=" + persistenceQuotient +
+            ", currentInferenceCount=" + currentInferenceCount +
+            ", inferenceConfig=" + inferenceConfig +
+            ", licenseLevel=" + licenseLevel +
+            ", trainedModelCircuitBreaker=" + trainedModelCircuitBreaker +
+            ", referenceCount=" + referenceCount +
+            '}';
+    }
 }