Add_tracking_metrics

ax/api/client.py

@@ -280,6 +280,33 @@ def configure_metrics(self, metrics: Sequence[IMetric]) -> None:
         """
         self._set_metrics(metrics=metrics)
 
+    def configure_tracking_metrics(self, metric_names: Sequence[str]) -> None:
+        """
+        Add tracking metrics to the ``Experiment`` by name.
+
+        Tracking metrics are metrics that are recorded during the experiment but
+        are not used as part of the ``OptimizationConfig`` (i.e., they are not
+        objectives or outcome constraints). Use this method to declare metrics
+        that you want to track alongside your optimization objectives.
+
+        If any of the metrics are already defined on the experiment, they will be
+        skipped with a warning.
+
+        Args:
+            metric_names: Names of metrics to be added as tracking metrics.
+
+        Saves to database on completion if ``storage_config`` is present.
+        """
+        for metric_name in metric_names:
+            if metric_name in self._experiment.metrics:
+                logger.warning(
+                    f"Metric {metric_name} already exists on experiment, skipping."
+                )
+                continue
+            self._experiment.add_tracking_metric(metric=Metric(name=metric_name))
+
+        self._save_experiment_to_db_if_possible(experiment=self._experiment)
+
     # -------------------- Section 1.2: Set (not API) -------------------------------
     def set_experiment(self, experiment: Experiment) -> None:
         """

ax/api/tests/test_client.py

@@ -421,6 +421,35 @@ def test_configure_metric(self) -> None:
             client._experiment.tracking_metrics[0],
         )
 
+    def test_configure_tracking_metrics(self) -> None:
+        """Test adding tracking metrics to an experiment."""
+        client = Client()
+
+        with self.assertRaisesRegex(AssertionError, "Experiment not set"):
+            client.configure_tracking_metrics(metric_names=["tracking1"])
+
+        client.configure_experiment(
+            parameters=[
+                RangeParameterConfig(name="x1", parameter_type="float", bounds=(0, 1))
+            ],
+            name="test_tracking_metrics",
+        )
+        client.configure_optimization(objective="objective")
+
+        # Test adding tracking metrics
+        client.configure_tracking_metrics(metric_names=["tracking1", "tracking2"])
+
+        # Verify tracking metrics were added
+        self.assertIn("tracking1", client._experiment.metrics)
+        self.assertIn("tracking2", client._experiment.metrics)
+        self.assertEqual(len(client._experiment.tracking_metrics), 2)
+
+        # Test that adding an existing metric logs a warning and skips it
+        with mock.patch("ax.api.client.logger.warning") as mock_logger:
+            client.configure_tracking_metrics(metric_names=["tracking1"])
+            mock_logger.assert_called_once()
+            self.assertIn("already exists", mock_logger.call_args[0][0])
+
     def test_set_experiment(self) -> None:
         client = Client()
         experiment = get_branin_experiment()