fixups

microsoft · Aug 20, 2024 · 057f553 · 057f553
1 parent 2ff1678
commit 057f553
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Showing 2 changed files with 14 additions and 6 deletions.
diff --git a/mlos_bench/mlos_bench/optimizers/convert_configspace.py b/mlos_bench/mlos_bench/optimizers/convert_configspace.py
@@ -26,7 +26,10 @@
 from mlos_bench.tunables.tunable import Tunable, TunableValue
 from mlos_bench.tunables.tunable_groups import TunableGroups
 from mlos_bench.util import try_parse_val
-from mlos_core.spaces.converters.util import QUANTIZATION_BINS_META_KEY
+from mlos_core.spaces.converters.util import (
+    QUANTIZATION_BINS_META_KEY,
+    monkey_patch_hp_quantization,
+)
 
 _LOG = logging.getLogger(__name__)
 
@@ -77,10 +80,6 @@ def _tunable_to_configspace(
     meta: Dict[Hashable, TunableValue] = {"cost": cost}
     if group_name is not None:
         meta["group"] = group_name
-    if tunable.is_numerical and tunable.quantization_bins:
-        # Temporary workaround to dropped quantization support in ConfigSpace 1.0
-        # See Also: https://github.com/automl/ConfigSpace/issues/390
-        meta[QUANTIZATION_BINS_META_KEY] = tunable.quantization_bins
 
     if tunable.type == "categorical":
         return ConfigurationSpace(
@@ -141,6 +140,14 @@ def _tunable_to_configspace(
     else:
         raise TypeError(f"Invalid Parameter Type: {tunable.type}")
 
+    if tunable.is_numerical and tunable.quantization_bins:
+        # Temporary workaround to dropped quantization support in ConfigSpace 1.0
+        # See Also: https://github.com/automl/ConfigSpace/issues/390
+        new_meta = dict(range_hp.meta or {})
+        new_meta[QUANTIZATION_BINS_META_KEY] = tunable.quantization_bins
+        range_hp.meta = new_meta
+        monkey_patch_hp_quantization(range_hp)
+
     if not tunable.special:
         return ConfigurationSpace({tunable.name: range_hp})
 

diff --git a/mlos_bench/mlos_bench/tests/tunables/tunable_to_configspace_test.py b/mlos_bench/mlos_bench/tests/tunables/tunable_to_configspace_test.py
@@ -13,7 +13,6 @@
     UniformFloatHyperparameter,
     UniformIntegerHyperparameter,
 )
-from ConfigSpace.hyperparameters import NumericalHyperparameter
 
 from mlos_bench.optimizers.convert_configspace import (
     TunableValueKind,
@@ -128,6 +127,8 @@ def _cmp_tunable_hyperparameter_numerical(tunable: Tunable, space: Configuration
     if tunable.in_range(tunable.value):
         assert param.default_value == tunable.value
     assert (param.meta or {}).get(QUANTIZATION_BINS_META_KEY) == tunable.quantization_bins
+    if tunable.quantization_bins:
+        assert param.sample_value() in list(tunable.quantized_values or [])
 
 
 def test_tunable_to_configspace_categorical(tunable_categorical: Tunable) -> None: