Validate required metrics in AxClient for complete trials, (uncommitt…

…ed/untracked changes), (uncommitted/untracked changes) (#2082)

Summary:
Pull Request resolved: #2082

Add a `_validate_all_required_metrics_present` and call in `AxClient.complete_trial` to ensure a trial has all required data to be marked `COMPLETE`

Reviewed By: saitcakmak, lena-kashtelyan

Differential Revision: D52057299

fbshipit-source-id: ecad7686b275f072579471c7b865589e5b61eb76

ax/service/ax_client.py

@@ -32,6 +32,7 @@
 from ax.core.arm import Arm
 from ax.core.base_trial import BaseTrial, TrialStatus
 from ax.core.experiment import DataType, Experiment
+from ax.core.formatting_utils import data_and_evaluations_from_raw_data
 from ax.core.generation_strategy_interface import GenerationStrategyInterface
 from ax.core.generator_run import GeneratorRun
 from ax.core.map_data import MapData
@@ -1626,7 +1627,16 @@ def _update_trial_with_raw_data(
         )
 
         if complete_trial:
-            trial.mark_completed()
+            if not self._validate_all_required_metrics_present(
+                raw_data=raw_data, trial_index=trial_index
+            ):
+                logger.warning(
+                    "Marking the trial as failed because it is missing one"
+                    "or more required metrics."
+                )
+                trial.mark_failed()
+            else:
+                trial.mark_completed()
 
         self._save_or_update_trial_in_db_if_possible(
             experiment=self.experiment,
@@ -1789,6 +1799,26 @@ def _find_last_trial_with_parameterization(
             f"No trial on experiment matches parameterization {parameterization}."
         )
 
+    def _validate_all_required_metrics_present(
+        self, raw_data: TEvaluationOutcome, trial_index: int
+    ) -> bool:
+        """Check if all required metrics are present in the given raw data."""
+        opt_config = self.experiment.optimization_config
+        if opt_config is None:
+            return True
+
+        _, data = data_and_evaluations_from_raw_data(
+            raw_data={"data": raw_data},
+            sample_sizes={},
+            trial_index=trial_index,
+            data_type=self.experiment.default_data_type,
+            metric_names=opt_config.objective.metric_names,
+        )
+        required_metrics = set(opt_config.metrics.keys())
+        provided_metrics = data.metric_names
+        missing_metrics = required_metrics - provided_metrics
+        return not missing_metrics
+
     @classmethod
     def _get_pending_observation_features(
         cls,

ax/service/tests/test_ax_client.py

@@ -1618,6 +1618,36 @@ def test_update_trial_data(self) -> None:
         df = ax_client.experiment.lookup_data_for_trial(idx)[0].df
         self.assertEqual(df["mean"].item(), 3.0)
 
+        # Incomplete trial fails
+        params, idx = ax_client.get_next_trial()
+        ax_client.complete_trial(trial_index=idx, raw_data={"missing_metric": (1, 0.0)})
+        self.assertTrue(ax_client.get_trial(idx).status.is_failed)
+
+    def test_incomplete_multi_fidelity_trial(self) -> None:
+        ax_client = AxClient()
+        ax_client.create_experiment(
+            parameters=[
+                {"name": "x", "type": "range", "bounds": [-5.0, 10.0]},
+                {"name": "y", "type": "range", "bounds": [0.0, 1.0]},
+            ],
+            minimize=True,
+            objective_name="branin",
+            support_intermediate_data=True,
+        )
+        # Trial with complete data
+        params, idx = ax_client.get_next_trial()
+        ax_client.complete_trial(
+            trial_index=idx, raw_data=[({"fidelity": 1}, {"branin": (123, 0.0)})]
+        )
+        self.assertTrue(ax_client.get_trial(idx).status.is_completed)
+        # Trial with incomplete data
+        params, idx = ax_client.get_next_trial()
+        ax_client.complete_trial(
+            trial_index=idx,
+            raw_data=[({"fidelity": 2}, {"missing_metric": (456, 0.0)})],
+        )
+        self.assertTrue(ax_client.get_trial(idx).status.is_failed)
+
     def test_trial_completion_with_metadata_with_iso_times(self) -> None:
         ax_client = get_branin_optimization()
         params, idx = ax_client.get_next_trial()