Always winsorize when no objective thresholds are specified (facebook…

…#1614)

Summary:
Pull Request resolved: facebook#1614

Winsorize a `MultiObjective` when the objective thresholds aren't specified.

Reviewed By: saitcakmak

Differential Revision: D45581780

fbshipit-source-id: 257a308cd23e396b9616ebb6c08130847f5f1092

ax/modelbridge/tests/test_winsorize_transform.py

@@ -496,7 +496,7 @@ def test_winsorization_with_optimization_config(self) -> None:
                     f"manually if you want to winsorize metric m{['1', '3'][i]}."
                     in [str(w.message) for w in ws]
                 )
-        # Multi-objective without objective thresholds (should print a warning)
+        # Multi-objective without objective thresholds should warn and winsorize
         moo_objective = MultiObjective(
             [Objective(m1, minimize=False), Objective(m2, minimize=True)]
         )
@@ -507,15 +507,15 @@ def test_winsorization_with_optimization_config(self) -> None:
                 observation_data=deepcopy(all_obsd),
                 optimization_config=optimization_config,
             )
-            for i in range(2):
+            for _ in range(2):
                 self.assertTrue(
-                    "Automatic winsorization isn't supported for an objective in "
-                    "`MultiObjective` without objective thresholds. Specify the "
-                    "winsorization settings manually if you want to winsorize "
-                    f"metric m{i + 1}." in [str(w.message) for w in ws]
+                    "Encountered a `MultiObjective` without objective thresholds. We "
+                    "will winsorize each objective separately. We strongly recommend "
+                    "specifying the objective thresholds when using multi-objective "
+                    "optimization." in [str(w.message) for w in ws]
                 )
-        self.assertEqual(transform.cutoffs["m1"], (-float("inf"), float("inf")))
-        self.assertEqual(transform.cutoffs["m2"], (-float("inf"), float("inf")))
+        self.assertEqual(transform.cutoffs["m1"], (-6.5, float("inf")))
+        self.assertEqual(transform.cutoffs["m2"], (-float("inf"), 10.0))
         self.assertEqual(transform.cutoffs["m3"], (-float("inf"), float("inf")))
         # Add relative objective thresholds (should raise an error)
         objective_thresholds = [

ax/modelbridge/transforms/winsorize.py

@@ -9,7 +9,7 @@
 from typing import Dict, List, Optional, Tuple, TYPE_CHECKING, Union
 
 import numpy as np
-from ax.core.objective import ScalarizedObjective
+from ax.core.objective import MultiObjective, ScalarizedObjective
 from ax.core.observation import Observation, ObservationData
 from ax.core.optimization_config import (
     MultiObjectiveOptimizationConfig,
@@ -272,12 +272,22 @@ def _get_auto_winsorization_cutoffs_multi_objective(
             metric_values=metric_values,
             outcome_constraints=objective_threshold,
         )
-    warnings.warn(
-        "Automatic winsorization isn't supported for an objective in `MultiObjective` "
-        "without objective thresholds. Specify the winsorization settings manually if "
-        f"you want to winsorize metric {metric_name}."
-    )
-    return DEFAULT_CUTOFFS  # Don't winsorize if there is no threshold
+    else:
+        warnings.warn(
+            "Encountered a `MultiObjective` without objective thresholds. We will "
+            "winsorize each objective separately. We strongly recommend specifying "
+            "the objective thresholds when using multi-objective optimization."
+        )
+        objectives = checked_cast(MultiObjective, optimization_config.objective)
+        minimize = [
+            objective.minimize
+            for objective in objectives.objectives
+            if objective.metric.name == metric_name
+        ][0]
+        return _get_auto_winsorization_cutoffs_single_objective(
+            metric_values=metric_values,
+            minimize=minimize,
+        )
 
 
 def _obtain_cutoffs_from_outcome_constraints(