Create new target in ax/adapter for parameter utils to limit deps (#5149)

Summary: Pull Request resolved: #5149

Reviewed By: Balandat

Differential Revision: D99688239

fbshipit-source-id: d30e8eee37e66840369aee8bbb471cb62902b662

Author: sdaulton

ax/adapter/adapter_utils.py

@@ -17,6 +17,10 @@
 import numpy as np
 import numpy.typing as npt
 import torch
+from ax.adapter.parameter_utils import (  # noqa: F401
+    can_map_to_binary,
+    is_unordered_choice,
+)
 from ax.adapter.transforms.base import Transform
 from ax.adapter.transforms.utils import (
     derelativize_optimization_config_with_raw_status_quo,
@@ -35,7 +39,7 @@
     OutcomeConstraint,
     ScalarizedOutcomeConstraint,
 )
-from ax.core.parameter import ChoiceParameter, Parameter, ParameterType, RangeParameter
+from ax.core.parameter import ChoiceParameter, ParameterType, RangeParameter
 from ax.core.parameter_constraint import ParameterConstraint
 from ax.core.search_space import SearchSpace, SearchSpaceDigest
 from ax.core.types import TBounds, TCandidateMetadata, TNumeric
@@ -1438,56 +1442,3 @@ def _consolidate_comparisons(X: Tensor, Y: Tensor) -> tuple[Tensor, Tensor]:
 
     X, Y, _ = consolidate_duplicates(X, Y)
     return X, Y
-
-
-def is_unordered_choice(
-    p: Parameter, min_choices: int | None = None, max_choices: int | None = None
-) -> bool:
-    """Returns whether a parameter is an unordered choice (categorical) parameter.
-
-    You can also specify `min_choices` and `max_choices` to restrict how many
-    possible values the parameter can take on.
-
-    Args:
-        p: Parameter.
-        min_choices: The minimum number of possible values for the parameter.
-        max_choices: The maximum number of possible values for the parameter.
-
-    Returns:
-        A boolean indicating whether p is an unordered choice parameter or not.
-    """
-    if min_choices is not None and min_choices < 0:
-        raise UserInputError("`min_choices` must be a non-negative integer.")
-    if max_choices is not None and max_choices < 0:
-        raise UserInputError("`max_choices` must be a non-negative integer.")
-    if (
-        min_choices is not None
-        and max_choices is not None
-        and min_choices > max_choices
-    ):
-        raise UserInputError("`min_choices` cannot be larger than `max_choices`.")
-    return (
-        isinstance(p, ChoiceParameter)
-        and not p.is_ordered
-        and (min_choices is None or min_choices <= len(p.values))
-        and (max_choices is None or max_choices >= len(p.values))
-    )
-
-
-def can_map_to_binary(p: Parameter) -> bool:
-    """Returns whether a parameter can be transformed to a binary parameter.
-
-    Any choice/range parameters with exactly two values can be transformed to a
-    binary parameter.
-
-    Args:
-        p: Parameter.
-
-    Returns
-        A boolean indicating whether p can be transformed to a binary parameter.
-    """
-    return (isinstance(p, ChoiceParameter) and len(p.values) == 2) or (
-        isinstance(p, RangeParameter)
-        and p.parameter_type == ParameterType.INT
-        and p.lower == p.upper - 1
-    )

ax/adapter/parameter_utils.py

@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+#
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-strict
+
+from __future__ import annotations
+
+from ax.core.parameter import ChoiceParameter, Parameter, ParameterType, RangeParameter
+from ax.exceptions.core import UserInputError
+
+
+def is_unordered_choice(
+    p: Parameter, min_choices: int | None = None, max_choices: int | None = None
+) -> bool:
+    """Returns whether a parameter is an unordered choice (categorical) parameter.
+
+    You can also specify `min_choices` and `max_choices` to restrict how many
+    possible values the parameter can take on.
+
+    Args:
+        p: Parameter.
+        min_choices: The minimum number of possible values for the parameter.
+        max_choices: The maximum number of possible values for the parameter.
+
+    Returns:
+        A boolean indicating whether p is an unordered choice parameter or not.
+    """
+    if min_choices is not None and min_choices < 0:
+        raise UserInputError("`min_choices` must be a non-negative integer.")
+    if max_choices is not None and max_choices < 0:
+        raise UserInputError("`max_choices` must be a non-negative integer.")
+    if (
+        min_choices is not None
+        and max_choices is not None
+        and min_choices > max_choices
+    ):
+        raise UserInputError("`min_choices` cannot be larger than `max_choices`.")
+    return (
+        isinstance(p, ChoiceParameter)
+        and not p.is_ordered
+        and (min_choices is None or min_choices <= len(p.values))
+        and (max_choices is None or max_choices >= len(p.values))
+    )
+
+
+def can_map_to_binary(p: Parameter) -> bool:
+    """Returns whether a parameter can be transformed to a binary parameter.
+
+    Any choice/range parameters with exactly two values can be transformed to a
+    binary parameter.
+
+    Args:
+        p: Parameter.
+
+    Returns
+        A boolean indicating whether p can be transformed to a binary parameter.
+    """
+    return (isinstance(p, ChoiceParameter) and len(p.values) == 2) or (
+        isinstance(p, RangeParameter)
+        and p.parameter_type == ParameterType.INT
+        and p.lower == p.upper - 1
+    )