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# ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
# pylint: disable=protected-access
from typing import Any, Dict, Optional, Union
from typing_extensions import Literal
from azure.ai.ml._restclient.v2023_06_01_preview.models import AzMonMonitoringAlertNotificationSettings
from azure.ai.ml._restclient.v2023_06_01_preview.models import MonitorDefinition as RestMonitorDefinition
from azure.ai.ml.constants._monitoring import (
AZMONITORING,
DEFAULT_DATA_DRIFT_SIGNAL_NAME,
DEFAULT_DATA_QUALITY_SIGNAL_NAME,
DEFAULT_PREDICTION_DRIFT_SIGNAL_NAME,
DEFAULT_TOKEN_USAGE_SIGNAL_NAME,
MonitorTargetTasks,
)
from azure.ai.ml.entities._mixins import RestTranslatableMixin
from azure.ai.ml.entities._monitoring.alert_notification import AlertNotification
from azure.ai.ml.entities._monitoring.compute import ServerlessSparkCompute
from azure.ai.ml.entities._monitoring.signals import (
CustomMonitoringSignal,
DataDriftSignal,
DataQualitySignal,
FeatureAttributionDriftSignal,
GenerationSafetyQualitySignal,
GenerationTokenStatisticsSignal,
MonitoringSignal,
PredictionDriftSignal,
)
from azure.ai.ml.entities._monitoring.target import MonitoringTarget
class MonitorDefinition(RestTranslatableMixin):
"""Monitor definition
:keyword compute: The Spark resource configuration to be associated with the monitor
:paramtype compute: ~azure.ai.ml.entities.SparkResourceConfiguration
:keyword monitoring_target: The ARM ID object associated with the model or deployment that is being monitored.
:paramtype monitoring_target: Optional[~azure.ai.ml.entities.MonitoringTarget]
:keyword monitoring_signals: The dictionary of signals to monitor. The key is the name of the signal and the value
is the DataSignal object. Accepted values for the DataSignal objects are DataDriftSignal, DataQualitySignal,
PredictionDriftSignal, FeatureAttributionDriftSignal, and CustomMonitoringSignal.
:paramtype monitoring_signals: Optional[Dict[str, Union[~azure.ai.ml.entities.DataDriftSignal
, ~azure.ai.ml.entities.DataQualitySignal, ~azure.ai.ml.entities.PredictionDriftSignal
, ~azure.ai.ml.entities.FeatureAttributionDriftSignal
, ~azure.ai.ml.entities.CustomMonitoringSignal
, ~azure.ai.ml.entities.GenerationSafetyQualitySignal
, ~azure.ai.ml.entities.GenerationTokenStatisticsSignal
, ~azure.ai.ml.entities.ModelPerformanceSignal]]]
:keyword alert_notification: The alert configuration for the monitor.
:paramtype alert_notification: Optional[Union[Literal['azmonitoring'], ~azure.ai.ml.entities.AlertNotification]]
.. admonition:: Example:
.. literalinclude:: ../samples/ml_samples_spark_configurations.py
:start-after: [START spark_monitor_definition]
:end-before: [END spark_monitor_definition]
:language: python
:dedent: 8
:caption: Creating Monitor definition.
"""
def __init__(
self,
*,
compute: ServerlessSparkCompute,
monitoring_target: Optional[MonitoringTarget] = None,
monitoring_signals: Dict[
str,
Union[
DataDriftSignal,
DataQualitySignal,
PredictionDriftSignal,
FeatureAttributionDriftSignal,
CustomMonitoringSignal,
GenerationSafetyQualitySignal,
GenerationTokenStatisticsSignal,
],
] = None, # type: ignore[assignment]
alert_notification: Optional[Union[Literal["azmonitoring"], AlertNotification]] = None,
) -> None:
self.compute = compute
self.monitoring_target = monitoring_target
self.monitoring_signals = monitoring_signals
self.alert_notification = alert_notification
def _to_rest_object(self, **kwargs: Any) -> RestMonitorDefinition:
default_data_window_size = kwargs.get("default_data_window_size")
ref_data_window_size = kwargs.get("ref_data_window_size")
rest_alert_notification = None
if self.alert_notification:
if isinstance(self.alert_notification, str) and self.alert_notification.lower() == AZMONITORING:
rest_alert_notification = AzMonMonitoringAlertNotificationSettings()
else:
if not isinstance(self.alert_notification, str):
rest_alert_notification = self.alert_notification._to_rest_object()
if self.monitoring_signals is not None:
_signals = {
signal_name: signal._to_rest_object(
default_data_window_size=default_data_window_size,
ref_data_window_size=ref_data_window_size,
)
for signal_name, signal in self.monitoring_signals.items()
}
return RestMonitorDefinition(
compute_configuration=self.compute._to_rest_object(),
monitoring_target=self.monitoring_target._to_rest_object() if self.monitoring_target else None,
signals=_signals, # pylint: disable=possibly-used-before-assignment
alert_notification_setting=rest_alert_notification,
)
@classmethod
def _from_rest_object(
cls, # pylint: disable=unused-argument
obj: RestMonitorDefinition,
**kwargs: Any,
) -> "MonitorDefinition":
from_rest_alert_notification: Any = None
if obj.alert_notification_setting:
if isinstance(obj.alert_notification_setting, AzMonMonitoringAlertNotificationSettings):
from_rest_alert_notification = AZMONITORING
else:
from_rest_alert_notification = AlertNotification._from_rest_object(obj.alert_notification_setting)
_monitoring_signals = {}
for signal_name, signal in obj.signals.items():
_monitoring_signals[signal_name] = MonitoringSignal._from_rest_object(signal)
return cls(
compute=ServerlessSparkCompute._from_rest_object(obj.compute_configuration),
monitoring_target=(
MonitoringTarget(
endpoint_deployment_id=obj.monitoring_target.deployment_id, ml_task=obj.monitoring_target.task_type
)
if obj.monitoring_target
else None
),
monitoring_signals=_monitoring_signals, # type: ignore[arg-type]
alert_notification=from_rest_alert_notification,
)
def _populate_default_signal_information(self) -> None:
if (
isinstance(self.monitoring_target, MonitoringTarget)
and self.monitoring_target.ml_task is not None
and self.monitoring_target.ml_task.lower()
== MonitorTargetTasks.QUESTION_ANSWERING.lower() # type: ignore[union-attr]
):
self.monitoring_signals = {
DEFAULT_TOKEN_USAGE_SIGNAL_NAME: GenerationTokenStatisticsSignal._get_default_token_statistics_signal(),
}
else:
self.monitoring_signals = {
DEFAULT_DATA_DRIFT_SIGNAL_NAME: DataDriftSignal._get_default_data_drift_signal(),
DEFAULT_PREDICTION_DRIFT_SIGNAL_NAME: PredictionDriftSignal._get_default_prediction_drift_signal(),
DEFAULT_DATA_QUALITY_SIGNAL_NAME: DataQualitySignal._get_default_data_quality_signal(),
}
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