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# ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
from typing import Optional, Union
from azure.ai.ml._restclient.v2023_06_01_preview.models import MonitoringTarget as RestMonitoringTarget
from azure.ai.ml.constants._monitoring import MonitorTargetTasks
class MonitoringTarget:
"""Monitoring target.
:keyword ml_task: Type of task. Allowed values: Classification, Regression, and QuestionAnswering
:paramtype ml_task: Optional[Union[str, MonitorTargetTasks]]
:keyword endpoint_deployment_id: The ARM ID of the target deployment. Mutually exclusive with model_id.
:paramtype endpoint_deployment_id: Optional[str]
:keyword model_id: ARM ID of the target model ID. Mutually exclusive with endpoint_deployment_id.
:paramtype model_id: Optional[str]
.. 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: Setting a monitoring target using endpoint_deployment_id.
"""
def __init__(
self,
*,
ml_task: Optional[Union[str, MonitorTargetTasks]] = None,
endpoint_deployment_id: Optional[str] = None,
model_id: Optional[str] = None,
):
self.endpoint_deployment_id = endpoint_deployment_id
self.model_id = model_id
self.ml_task = ml_task
def _to_rest_object(self) -> RestMonitoringTarget:
return RestMonitoringTarget(
task_type=self.ml_task if self.ml_task else "classification",
deployment_id=self.endpoint_deployment_id,
model_id=self.model_id,
)
@classmethod
def _from_rest_object(cls, obj: RestMonitoringTarget) -> "MonitoringTarget":
return cls(
ml_task=obj.task_type,
endpoint_deployment_id=obj.endpoint_deployment_id,
model_id=obj.model_id,
)
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