MoMo API review changes (#34480) (#34509)

* review changes (#34480)

* address comment

Author: nemanjarajic

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_monitoring/compute.py

@@ -26,7 +26,7 @@ def __init__(
         self.instance_type = instance_type
 
     def _to_rest_object(self) -> MonitorServerlessSparkCompute:
-        self.validate()
+        self._validate()
         return MonitorServerlessSparkCompute(
             runtime_version=self.runtime_version,
             instance_type=self.instance_type,
@@ -42,7 +42,7 @@ def _from_rest_object(cls, obj: MonitorServerlessSparkCompute) -> "ServerlessSpa
             instance_type=obj.instance_type,
         )
 
-    def validate(self) -> None:
+    def _validate(self) -> None:
         if self.runtime_version != "3.3":
             msg = "Compute runtime version must be 3.3"
             err = ValidationException(

sdk/ml/azure-ai-ml/azure/ai/ml/entities/_monitoring/thresholds.py

@@ -104,13 +104,6 @@ def _get_default_thresholds(cls) -> "NumericalDriftMetrics":
             normalized_wasserstein_distance=0.1,
         )
 
-    @classmethod
-    def defaults(cls) -> "NumericalDriftMetrics":
-        return cls._get_default_thresholds()
-
-    def get_name_and_threshold(self) -> Tuple:
-        return self._find_name_and_threshold()
-
 
 class CategoricalDriftMetrics(RestTranslatableMixin):
     """Categorical Drift Metrics
@@ -169,10 +162,6 @@ def _get_default_thresholds(cls) -> "CategoricalDriftMetrics":
             jensen_shannon_distance=0.1,
         )
 
-    @classmethod
-    def defaults(cls) -> "CategoricalDriftMetrics":
-        return cls._get_default_thresholds()
-
     def get_name_and_threshold(self) -> Tuple:
         return self._find_name_and_threshold()
 
@@ -204,15 +193,15 @@ def __init__(
     def _to_rest_object(self) -> DataDriftMetricThresholdBase:
         thresholds = []
         if self.numerical:
-            num_metric_name, num_threshold = self.numerical.get_name_and_threshold()
+            num_metric_name, num_threshold = self.numerical._find_name_and_threshold()
             thresholds.append(
                 NumericalDataDriftMetricThreshold(
                     metric=snake_to_camel(num_metric_name),
                     threshold=num_threshold,
                 )
             )
         if self.categorical:
-            cat_metric_name, cat_threshold = self.categorical.get_name_and_threshold()
+            cat_metric_name, cat_threshold = self.categorical._find_name_and_threshold()
             thresholds.append(
                 CategoricalDataDriftMetricThreshold(
                     metric=snake_to_camel(cat_metric_name),
@@ -244,8 +233,8 @@ def _from_rest_object(cls, obj: DataDriftMetricThresholdBase) -> "DataDriftMetri
     @classmethod
     def _get_default_thresholds(cls) -> "DataDriftMetricThreshold":
         return cls(
-            numerical=NumericalDriftMetrics.defaults(),
-            categorical=CategoricalDriftMetrics.defaults(),
+            numerical=NumericalDriftMetrics._get_default_thresholds(),
+            categorical=CategoricalDriftMetrics._get_default_thresholds(),
         )
 
     def __eq__(self, other: Any) -> bool:
@@ -279,15 +268,15 @@ def __init__(
     def _to_rest_object(self) -> PredictionDriftMetricThresholdBase:
         thresholds = []
         if self.numerical:
-            num_metric_name, num_threshold = self.numerical.get_name_and_threshold()
+            num_metric_name, num_threshold = self.numerical._find_name_and_threshold()
             thresholds.append(
                 NumericalPredictionDriftMetricThreshold(
                     metric=snake_to_camel(num_metric_name),
                     threshold=num_threshold,
                 )
             )
         if self.categorical:
-            cat_metric_name, cat_threshold = self.categorical.get_name_and_threshold()
+            cat_metric_name, cat_threshold = self.categorical._find_name_and_threshold()
             thresholds.append(
                 CategoricalPredictionDriftMetricThreshold(
                     metric=snake_to_camel(cat_metric_name),
@@ -319,8 +308,8 @@ def _from_rest_object(cls, obj: PredictionDriftMetricThresholdBase) -> "Predicti
     @classmethod
     def _get_default_thresholds(cls) -> "PredictionDriftMetricThreshold":
         return cls(
-            numerical=NumericalDriftMetrics.defaults(),
-            categorical=CategoricalDriftMetrics.defaults(),
+            numerical=NumericalDriftMetrics._get_default_thresholds(),
+            categorical=CategoricalDriftMetrics._get_default_thresholds(),
         )
 
     def __eq__(self, other: Any) -> bool:
@@ -404,10 +393,6 @@ def _get_default_thresholds(cls) -> "DataQualityMetricsNumerical":
             out_of_bounds_rate=0.0,
         )
 
-    @classmethod
-    def defaults(cls) -> "DataQualityMetricsNumerical":
-        return cls._get_default_thresholds()
-
 
 class DataQualityMetricsCategorical(RestTranslatableMixin):
     """Data Quality Categorical Metrics
@@ -480,10 +465,6 @@ def _get_default_thresholds(cls) -> "DataQualityMetricsCategorical":
             out_of_bounds_rate=0.0,
         )
 
-    @classmethod
-    def defaults(cls) -> "DataQualityMetricsCategorical":
-        return cls._get_default_thresholds()
-
 
 class DataQualityMetricThreshold(MetricThreshold):
     """Data quality metric threshold