two version of R2R are here HEAD master

1 files changed, 53 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_job/sweep/objective.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_job/sweep/objective.py
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+++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_job/sweep/objective.py
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+# ---------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# ---------------------------------------------------------
+from typing import Optional
+
+from azure.ai.ml._restclient.v2023_08_01_preview.models import Objective as RestObjective
+from azure.ai.ml.entities._mixins import RestTranslatableMixin
+
+
+class Objective(RestTranslatableMixin):
+    """Optimization objective.
+
+    :param goal: Defines supported metric goals for hyperparameter tuning. Accepted values
+     are: "minimize", "maximize".
+    :type goal: str
+    :param primary_metric: The name of the metric to optimize.
+    :type primary_metric: str
+
+    .. admonition:: Example:
+
+        .. literalinclude:: ../samples/ml_samples_sweep_configurations.py
+            :start-after: [START configure_sweep_job_bayesian_sampling_algorithm]
+            :end-before: [END configure_sweep_job_bayesian_sampling_algorithm]
+            :language: python
+            :dedent: 8
+            :caption: Assigning an objective to a SweepJob.
+    """
+
+    def __init__(self, goal: Optional[str], primary_metric: Optional[str] = None) -> None:
+        """Optimization objective.
+
+        :param goal: Defines supported metric goals for hyperparameter tuning. Acceptable values
+            are: "minimize" or "maximize".
+        :type goal: str
+        :param primary_metric: The name of the metric to optimize.
+        :type primary_metric: str
+        """
+        if goal is not None:
+            self.goal = goal.lower()
+        self.primary_metric = primary_metric
+
+    def _to_rest_object(self) -> RestObjective:
+        return RestObjective(
+            goal=self.goal,
+            primary_metric=self.primary_metric,
+        )
+
+    @classmethod
+    def _from_rest_object(cls, obj: RestObjective) -> Optional["Objective"]:
+        if not obj:
+            return None
+
+        return cls(goal=obj.goal, primary_metric=obj.primary_metric)