Raise DataRequiredError from transforms that need data but did not …

…get it

Summary: Unlike a generic `ValueError`, `DataRequiredError` is handled in generation strategy, scheduler, and AxService API. In `Scheduler`, that error type will make the scheduler wait instead of failing.

Reviewed By: bernardbeckerman

Differential Revision: D35853790

fbshipit-source-id: 4008a5beca402f74aadde47ec8d3687494151da1

ax/modelbridge/tests/test_percentile_y_transform.py

@@ -8,6 +8,7 @@
 
 import numpy as np
 from ax.core.observation import ObservationData
+from ax.exceptions.core import DataRequiredError
 from ax.modelbridge.transforms.percentile_y import PercentileY
 from ax.utils.common.testutils import TestCase
 
@@ -67,7 +68,7 @@ def setUp(self):
         )
 
     def testInit(self):
-        with self.assertRaises(ValueError):
+        with self.assertRaises(DataRequiredError):
             PercentileY(search_space=None, observation_features=[], observation_data=[])
 
     def testTransformObservations(self):

ax/modelbridge/tests/test_standardize_y_transform.py

@@ -14,6 +14,7 @@
 from ax.core.optimization_config import OptimizationConfig
 from ax.core.outcome_constraint import OutcomeConstraint, ScalarizedOutcomeConstraint
 from ax.core.types import ComparisonOp
+from ax.exceptions.core import DataRequiredError
 from ax.modelbridge.transforms.standardize_y import StandardizeY
 from ax.utils.common.testutils import TestCase
 
@@ -46,7 +47,7 @@ def setUp(self):
     def testInit(self):
         self.assertEqual(self.t.Ymean, {"m1": 1.0, "m2": 1.5})
         self.assertEqual(self.t.Ystd, {"m1": 1.0, "m2": sqrt(1 / 3)})
-        with self.assertRaises(ValueError):
+        with self.assertRaises(DataRequiredError):
             StandardizeY(
                 search_space=None, observation_features=None, observation_data=[]
             )

ax/modelbridge/tests/test_winsorize_transform.py

@@ -21,6 +21,7 @@
     OutcomeConstraint,
     ScalarizedOutcomeConstraint,
 )
+from ax.exceptions.core import DataRequiredError
 from ax.exceptions.core import UnsupportedError, UserInputError
 from ax.modelbridge.transforms.winsorize import (
     _get_auto_winsorization_cutoffs_outcome_constraint,
@@ -146,7 +147,8 @@ def testInit(self):
         self.assertEqual(self.t2.cutoffs["m1"], (0.0, float("inf")))
         self.assertEqual(self.t2.cutoffs["m2"], (0.0, float("inf")))
         with self.assertRaisesRegex(
-            ValueError, "Winsorize transform requires non-empty observation data."
+            DataRequiredError,
+            "`Winsorize` transform requires non-empty observation data.",
         ):
             Winsorize(search_space=None, observation_features=[], observation_data=[])
         obsd = [deepcopy(self.obsd1)]

ax/modelbridge/tests/test_winsorize_transform_legacy.py

@@ -9,6 +9,7 @@
 
 import numpy as np
 from ax.core.observation import ObservationData
+from ax.exceptions.core import DataRequiredError
 from ax.modelbridge.transforms.winsorize import Winsorize
 from ax.utils.common.testutils import TestCase
 
@@ -131,7 +132,7 @@ def testInit(self):
         self.assertEqual(self.t1.cutoffs["m2"], (-float("inf"), 1.0))
         self.assertEqual(self.t2.cutoffs["m1"], (0.0, float("inf")))
         self.assertEqual(self.t2.cutoffs["m2"], (0.0, float("inf")))
-        with self.assertRaises(ValueError):
+        with self.assertRaises(DataRequiredError):
             Winsorize(search_space=None, observation_features=[], observation_data=[])
 
     def testTransformObservations(self):

ax/modelbridge/transforms/percentile_y.py

@@ -9,13 +9,15 @@
 
 from ax.core.observation import ObservationData, ObservationFeatures
 from ax.core.search_space import SearchSpace
+from ax.exceptions.core import DataRequiredError
 from ax.modelbridge.transforms.base import Transform
 from ax.modelbridge.transforms.utils import get_data
 from ax.models.types import TConfig
 from ax.utils.common.logger import get_logger
 from ax.utils.common.typeutils import checked_cast
 from scipy import stats
 
+
 if TYPE_CHECKING:
     # import as module to make sphinx-autodoc-typehints happy
     from ax import modelbridge as modelbridge_module  # noqa F401  # pragma: no cover
@@ -37,7 +39,7 @@ def __init__(
         config: Optional[TConfig] = None,
     ) -> None:
         if len(observation_data) == 0:
-            raise ValueError(
+            raise DataRequiredError(
                 "Percentile transform requires non-empty observation data."
             )
         metric_values = get_data(observation_data=observation_data)

ax/modelbridge/transforms/standardize_y.py

@@ -12,6 +12,7 @@
 from ax.core.outcome_constraint import ScalarizedOutcomeConstraint
 from ax.core.search_space import SearchSpace
 from ax.core.types import TParamValue
+from ax.exceptions.core import DataRequiredError
 from ax.modelbridge.transforms.base import Transform
 from ax.modelbridge.transforms.utils import get_data
 from ax.models.types import TConfig
@@ -41,8 +42,8 @@ def __init__(
         config: Optional[TConfig] = None,
     ) -> None:
         if len(observation_data) == 0:
-            raise ValueError(
-                "StandardizeY transform requires non-empty observation data."
+            raise DataRequiredError(
+                "`StandardizeY` transform requires non-empty observation data."
             )
         Ys = get_data(observation_data=observation_data)
         # Compute means and SDs

ax/modelbridge/transforms/winsorize.py

@@ -22,6 +22,7 @@
     ScalarizedOutcomeConstraint,
 )
 from ax.core.search_space import SearchSpace
+from ax.exceptions.core import DataRequiredError
 from ax.exceptions.core import UnsupportedError, UserInputError
 from ax.modelbridge.transforms.base import Transform
 from ax.modelbridge.transforms.utils import get_data
@@ -114,7 +115,9 @@ def __init__(
         config: Optional[TConfig] = None,
     ) -> None:
         if len(observation_data) == 0:
-            raise ValueError("Winsorize transform requires non-empty observation data.")
+            raise DataRequiredError(
+                "`Winsorize` transform requires non-empty observation data."
+            )
         if config is None:
             raise ValueError(
                 "Transform config for `Winsorize` transform must be specified and "