Add an option to override ModelSpec.model_key

Summary:
Most of our models now utilize MBM, which can represent many different models using the same Models.BOTORCH_MODULAR. Being able to overwrite the default model key "BoTorch" will allow us to be more expressive about what model was used to generate a given candidate.

Follow-up diff will utilize this to require unique model key for each ModelSpec in a GenerationNode, which will ensure identifiability when multiple MBM models are used with model selection.

Differential Revision: D61984169

ax/modelbridge/model_spec.py

@@ -20,7 +20,7 @@
 from ax.core.observation import ObservationFeatures
 from ax.core.optimization_config import OptimizationConfig
 from ax.core.search_space import SearchSpace
-from ax.exceptions.core import UserInputError
+from ax.exceptions.core import AxWarning, UserInputError
 from ax.modelbridge.base import ModelBridge
 from ax.modelbridge.cross_validation import (
     compute_diagnostics,
@@ -61,6 +61,9 @@ class ModelSpec(SortableBase, SerializationMixin):
     model_gen_kwargs: dict[str, Any] = field(default_factory=dict)
     # Kwargs to pass to `cross_validate`.
     model_cv_kwargs: dict[str, Any] = field(default_factory=dict)
+    # An optional override for the model key. Each `ModelSpec` in a
+    # `GenerationNode` must have a unique key to ensure identifiability.
+    model_key_override: Optional[str] = None
 
     # Fitted model, constructed using specified `model_kwargs` and `Data`
     # on `ModelSpec.fit`
@@ -106,12 +109,10 @@ def fixed_features(self, value: Optional[ObservationFeatures]) -> None:
     @property
     def model_key(self) -> str:
         """Key string to identify the model used by this ``ModelSpec``."""
-        # NOTE: In the future, might need to add more to model key to make
-        # model specs with the same model (but different kwargs) easier to
-        # distinguish from their key. Could also add separate property, just
-        # `key` (for `ModelSpec.key`, which will be unique even between model
-        # specs with same model type).
-        return self.model_enum.value
+        if self.model_key_override is not None:
+            return self.model_key_override
+        else:
+            return self.model_enum.value
 
     def fit(
         self,
@@ -342,23 +343,24 @@ def __post_init__(self) -> None:
                 "as the required `factory_function` argument to "
                 "`FactoryFunctionModelSpec`."
             )
+        if self.model_key_override is None:
+            try:
+                # `model` is defined via a factory function.
+                # pyre-ignore[16]: Anonymous callable has no attribute `__name__`.
+                self.model_key_override = not_none(self.factory_function).__name__
+            except Exception:
+                raise TypeError(
+                    f"{self.factory_function} is not a valid function, cannot extract "
+                    "name. Please provide the model name using `model_key_override`."
+                )
+
         warnings.warn(
             "Using a factory function to describe the model, so optimization state "
             "cannot be stored and optimization is not resumable if interrupted.",
+            AxWarning,
             stacklevel=3,
         )
 
-    @property
-    def model_key(self) -> str:
-        """Key string to identify the model used by this ``ModelSpec``."""
-        try:
-            # `model` is defined via a factory function.
-            return not_none(self.factory_function).__name__  # pyre-ignore[16]
-        except Exception:
-            raise TypeError(
-                f"{self.factory_function} is not a valid function, cannot extract name."
-            )
-
     def fit(
         self,
         experiment: Experiment,

ax/modelbridge/tests/test_model_spec.py

@@ -67,8 +67,12 @@ def test_fit(self, wrapped_extract_ssd: Mock) -> None:
         wrapped_extract_ssd.assert_called_once()
 
     def test_model_key(self) -> None:
-        ms = ModelSpec(model_enum=Models.GPEI)
-        self.assertEqual(ms.model_key, "GPEI")
+        ms = ModelSpec(model_enum=Models.BOTORCH_MODULAR)
+        self.assertEqual(ms.model_key, "BoTorch")
+        ms = ModelSpec(
+            model_enum=Models.BOTORCH_MODULAR, model_key_override="MBM with defaults"
+        )
+        self.assertEqual(ms.model_key, "MBM with defaults")
 
     @patch(f"{ModelSpec.__module__}.compute_diagnostics")
     @patch(f"{ModelSpec.__module__}.cross_validate", return_value=["fake-cv-result"])
@@ -194,3 +198,10 @@ def test_construct(self) -> None:
     def test_model_key(self) -> None:
         ms = FactoryFunctionModelSpec(factory_function=get_sobol)
         self.assertEqual(ms.model_key, "get_sobol")
+        with self.assertRaisesRegex(TypeError, "cannot extract name"):
+            # pyre-ignore[6] - Invalid factory function for testing.
+            FactoryFunctionModelSpec(factory_function="test")
+        ms = FactoryFunctionModelSpec(
+            factory_function=get_sobol, model_key_override="fancy sobol"
+        )
+        self.assertEqual(ms.model_key, "fancy sobol")