making classes public (Azure#31922)

Author: MilesHolland

sdk/ml/azure-ai-ml/azure/ai/ml/constants/__init__.py

@@ -28,6 +28,7 @@
     MonitorModelType,
     MonitorFeatureType,
     MonitorDatasetContext,
+    MonitorTargetTasks,
 )
 
 TabularTrainingMode.__module__ = __name__
@@ -57,5 +58,6 @@
     "MonitorModelType",
     "MonitorFeatureType",
     "MonitorDatasetContext",
+    "MonitorTargetTasks",
     "IPProtectionLevel",
 ]

sdk/ml/azure-ai-ml/azure/ai/ml/entities/__init__.py

@@ -51,6 +51,7 @@
     UsernamePasswordConfiguration,
     AccessKeyConfiguration,
     ApiKeyConfiguration,
+    NoneCredentialConfiguration,
 )
 from ._datastore.adls_gen1 import AzureDataLakeGen1Datastore
 from ._datastore.azure_storage import AzureBlobDatastore, AzureDataLakeGen2Datastore, AzureFileDatastore
@@ -165,6 +166,7 @@
     PackageInputPathVersion,
 )
 from ._monitoring.alert_notification import AlertNotification
+from ._monitoring.compute import ServerlessSparkCompute
 from ._monitoring.definition import MonitorDefinition
 from ._monitoring.input_data import MonitorInputData
 from ._monitoring.schedule import MonitorSchedule
@@ -176,6 +178,9 @@
     CustomMonitoringSignal,
     MonitorFeatureFilter,
     DataSegment,
+    FADProductionData,
+    ProductionData,
+    ReferenceData,
 )
 from ._monitoring.target import MonitoringTarget
 from ._monitoring.thresholds import (
@@ -184,6 +189,8 @@
     PredictionDriftMetricThreshold,
     FeatureAttributionDriftMetricThreshold,
     CustomMonitoringMetricThreshold,
+    CategoricalDriftMetrics,
+    NumericalDriftMetrics,
 )
 
 from ._workspace_hub.workspace_hub import WorkspaceHub, WorkspaceHubConfig
@@ -397,6 +404,7 @@
     "Route",
     "AccessKeyConfiguration",
     "AlertNotification",
+    "ServerlessSparkCompute",
     "ApiKeyConfiguration",
     "MonitorDefinition",
     "MonitorInputData",
@@ -408,14 +416,20 @@
     "CustomMonitoringSignal",
     "MonitorFeatureFilter",
     "DataSegment",
+    "FADProductionData",
+    "ProductionData",
+    "ReferenceData",
     "MonitoringTarget",
     "DataDriftMetricThreshold",
     "DataQualityMetricThreshold",
     "PredictionDriftMetricThreshold",
     "FeatureAttributionDriftMetricThreshold",
     "CustomMonitoringMetricThreshold",
+    "CategoricalDriftMetrics",
+    "NumericalDriftMetrics",
     "DataCollector",
     "IntellectualProperty",
     "DeploymentCollection",
     "RequestLogging",
+    "NoneCredentialConfiguration",
 ]

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

@@ -288,8 +288,6 @@ class MonitoringSignal(RestTranslatableMixin):
 
     This class should not be instantiated directly. Instead, use one of its subclasses.
 
-    :keyword target_dataset: The target dataset definition for monitor input.
-    :paramtype target_dataset: ~azure.ai.ml.entities.TargetDataset
     :keyword baseline_dataset: The baseline dataset definition for monitor input.
     :paramtype baseline_dataset: ~azure.ai.ml.entities.MonitorInputData
     :keyword metric_thresholds: The metric thresholds for the signal.
@@ -351,8 +349,6 @@ class DataSignal(MonitoringSignal):
 
     This class should not be instantiated directly. Instead, use one of its subclasses.
 
-    :keyword target_dataset: The target dataset definition for monitor input.
-    :paramtype target_dataset: ~azure.ai.ml.entities.TargetDataset
     :keyword baseline_dataset: The baseline dataset definition for monitor input.
     :paramtype baseline_dataset: ~azure.ai.ml.entities.MonitorInputData
     :keyword features: The features to include in the signal.
@@ -484,8 +480,6 @@ class PredictionDriftSignal(MonitoringSignal):
     :vartype type: str
     :keyword baseline_dataset: The dataset to calculate drift against.
     :paramtype baseline_dataset: ~azure.ai.ml.entities.MonitorInputData
-    :keyword target_dataset: The dataset for which drift will be calculated.
-    :paramtype target_dataset: ~azure.ai.ml.entities.TargetDataset
     :keyword metric_thresholds: A list of metrics to calculate and their associated thresholds
     :paramtype metric_thresholds: list[~azure.ai.ml.entities.PredictionDriftMetricThreshold]
     :keyword alert_enabled: Whether or not to enable alerts for the signal. Defaults to True.
@@ -548,8 +542,6 @@ class DataQualitySignal(DataSignal):
 
     :ivar type: The type of the signal. Set to "data_quality" for this class.
     :vartype type: str
-    :keyword target_dataset: The data for which quality will be calculated.
-    :paramtype target_dataset: ~azure.ai.ml.entities.TargetDataset
     :keyword baseline_dataset: The data to calculate quality against.
     :paramtype baseline_dataset: ~azure.ai.ml.entities.MonitorInputData
     :keyword metric_thresholds: A list of metrics to calculate and their
@@ -632,8 +624,6 @@ class ModelSignal(MonitoringSignal):
 
     This class should not be instantiated directly. Instead, use one of its subclasses.
 
-    :keyword target_dataset: The data for which quality will be calculated.
-    :paramtype target_dataset: ~azure.ai.ml.entities.TargetDataset
     :keyword baseline_dataset: The data to calculate quality against.
     :paramtype baseline_dataset: ~azure.ai.ml.entities.MonitorInputData
     :keyword metric_thresholds: A list of metrics to calculate and their
@@ -717,8 +707,6 @@ class FeatureAttributionDriftSignal(RestTranslatableMixin):
 
     :ivar type: The type of the signal. Set to "feature_attribution_drift" for this class.
     :vartype type: str
-    :keyword target_dataset: The data for which drift will be calculated.
-    :paramtype target_dataset: ~azure.ai.ml.entities.TargetDataset
     :keyword baseline_dataset: The data to calculate drift against.
     :paramtype baseline_dataset: ~azure.ai.ml.entities.MonitorInputData
     :keyword metric_thresholds: A list of metrics to calculate and their
@@ -774,8 +762,6 @@ def _from_rest_object(cls, obj: RestFeatureAttributionDriftMonitoringSignal) ->
 class ModelPerformanceSignal(ModelSignal):
     """Model performance signal.
 
-    :keyword target_dataset: The data for which performance will be calculated.
-    :paramtype target_dataset: ~azure.ai.ml.entities.TargetDataset
     :keyword baseline_dataset: The data to calculate performance against.
     :paramtype baseline_dataset: ~azure.ai.ml.entities.MonitorInputData
     :keyword metric_thresholds: A list of metrics to calculate and their