feat: add default_skew_threshold to TrainingPredictionSkewDetectionConfig in aiplatform v1beta1, v1 model_monitoring.proto

Google APIs · copybara-github · commit db1cd5e9cdf8 · 2022-06-15T10:34:19.000-07:00
feat: add default_drift_threshold to PredictionDriftDetectionConfig in aiplatform v1beta1, v1 model_monitoring.proto
PiperOrigin-RevId: 455164942
diff --git a/google/cloud/aiplatform/v1/model_monitoring.proto b/google/cloud/aiplatform/v1/model_monitoring.proto
@@ -82,6 +82,11 @@ message ModelMonitoringObjectiveConfig {
     // against attribution score distance between the training and prediction
     // feature.
     map<string, ThresholdConfig> attribution_score_skew_thresholds = 2;
+
+    // Skew anomaly detection threshold used by all features.
+    // When the per-feature thresholds are not set, this field can be used to
+    // specify a threshold for all features.
+    ThresholdConfig default_skew_threshold = 6;
   }
 
   // The config for Prediction data drift detection.
@@ -95,6 +100,11 @@ message ModelMonitoringObjectiveConfig {
     // Key is the feature name and value is the threshold. The threshold here is
     // against attribution score distance between different time windows.
     map<string, ThresholdConfig> attribution_score_drift_thresholds = 2;
+
+    // Drift anomaly detection threshold used by all features.
+    // When the per-feature thresholds are not set, this field can be used to
+    // specify a threshold for all features.
+    ThresholdConfig default_drift_threshold = 5;
   }
 
   // The config for integrating with Vertex Explainable AI. Only applicable if
diff --git a/google/cloud/aiplatform/v1beta1/model_monitoring.proto b/google/cloud/aiplatform/v1beta1/model_monitoring.proto
@@ -82,6 +82,11 @@ message ModelMonitoringObjectiveConfig {
     // against attribution score distance between the training and prediction
     // feature.
     map<string, ThresholdConfig> attribution_score_skew_thresholds = 2;
+
+    // Skew anomaly detection threshold used by all features.
+    // When the per-feature thresholds are not set, this field can be used to
+    // specify a threshold for all features.
+    ThresholdConfig default_skew_threshold = 6;
   }
 
   // The config for Prediction data drift detection.
@@ -95,6 +100,11 @@ message ModelMonitoringObjectiveConfig {
     // Key is the feature name and value is the threshold. The threshold here is
     // against attribution score distance between different time windows.
     map<string, ThresholdConfig> attribution_score_drift_thresholds = 2;
+
+    // Drift anomaly detection threshold used by all features.
+    // When the per-feature thresholds are not set, this field can be used to
+    // specify a threshold for all features.
+    ThresholdConfig default_drift_threshold = 5;
   }
 
   // The config for integrating with Vertex Explainable AI. Only applicable if
