Merge pull request #167 from automl/upgrade-configspace

Upgrade ConfigCpace to v1.2.0

.pre-commit-config.yaml

@@ -48,13 +48,15 @@ repos:
             'absl-py>=1.0.0',
             'jsonlines>=3.0.0',
             'pandas>=1.3.4',
-            'numpy==1.26.4',
-            'matplotlib>=3.5.1',
+            'numpy>=2.0.1',
+            'matplotlib==3.9.0',
+            'seaborn>=0.13.0',
             'pyyaml>=6.0.1',
             'kaleido>=0.2.1',
             'gplearn>=0.4.2',
             'sympy>=1.12',
-            'ConfigSpace==0.6.1',
+            'requests>=2.31.0',
+            'ConfigSpace==1.2.0',
             'pyrfr>=0.9.0',
             'hpbandster==0.7.4',
             'dash==2.0.0',
@@ -63,6 +65,8 @@ repos:
             'redis>=4.1.4',
             'rq>=1.10.1',
             'werkzeug==2.0.3',
+            'pyarrow==16.1.0',
+            'fastparquet==2024.5.0',
             'pyPDPPartitioner>=0.1.8'
         ] # Needed for mypy, so that it knows the types to check
 

CHANGELOG.md

@@ -3,6 +3,10 @@
 ## Converters
 - Add support for AMLTK.
 
+## Version-Updates
+- ConfigSpace from 0.6.1 to 1.2.0
+- Numpy from 1.26.4 to 2.0.1
+
 ## Ablation Paths
 - Added ablation paths as a plugin.
 - Added ablation as a evaluator to use for the plugin.

README.md

@@ -72,7 +72,7 @@ from deepcave import Recorder, Objective
 configspace = CS.ConfigurationSpace(seed=0)
 alpha = CS.hyperparameters.UniformFloatHyperparameter(
     name='alpha', lower=0, upper=1)
-configspace.add_hyperparameter(alpha)
+configspace.add(alpha)
 
 accuracy = Objective("accuracy", lower=0, upper=1, optimize="upper")
 mse = Objective("mse", lower=0)

deepcave/evaluators/epm/random_forest.py

@@ -430,7 +430,7 @@ def _predict(self, X: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
             # Transform list of 2d arrays into a 3d array
             num_trees = self._model.options.num_trees
             shape = (X.shape[0], num_trees, third_dimension)
-            preds_as_array = np.zeros(shape) * np.NaN
+            preds_as_array = np.zeros(shape) * np.nan
             for i, preds_per_tree in enumerate(all_preds):
                 for j, pred in enumerate(preds_per_tree):
                     preds_as_array[i, j, : len(pred)] = pred

deepcave/evaluators/epm/utils.py

@@ -6,7 +6,7 @@
 as well as the bounds of the Hyperparameters.
 """
 
-import typing
+from typing import List, Optional, Tuple
 
 import numpy as np
 from ConfigSpace import ConfigurationSpace
@@ -25,8 +25,8 @@
 
 def get_types(
     config_space: ConfigurationSpace,
-    instance_features: typing.Optional[np.ndarray] = None,
-) -> typing.Tuple[typing.List[int], typing.List[typing.Tuple[float, float]]]:
+    instance_features: Optional[np.ndarray] = None,
+) -> Tuple[List[int], List[Tuple[float, float]]]:
     """
     Return the types of the Hyperparameters.
 
@@ -42,7 +42,7 @@ def get_types(
 
     Returns
     -------
-    Tuple[typing.List[int], List[Tuple[float, float]]]
+    Tuple[List[int], List[Tuple[float, float]]]
         The types of the Hyperparameters, as well as the bounds and instance features.
 
     Raises
@@ -104,28 +104,28 @@ def get_types(
                     "Inactive parameters not supported for Beta and Normal Hyperparameters"
                 )
 
-            bounds[i] = (param._lower, param._upper)
+            bounds[i] = (param.lower_vectorized, param.upper_vectorized)  # type: ignore
         elif isinstance(param, NormalIntegerHyperparameter):
             if can_be_inactive:
                 raise ValueError(
                     "Inactive parameters not supported for Beta and Normal Hyperparameters"
                 )
 
-            bounds[i] = (param.nfhp._lower, param.nfhp._upper)
+            bounds[i] = (param.lower_vectorized, param.upper_vectorized)  # type: ignore
         elif isinstance(param, BetaFloatHyperparameter):
             if can_be_inactive:
                 raise ValueError(
                     "Inactive parameters not supported for Beta and Normal Hyperparameters"
                 )
 
-            bounds[i] = (param._lower, param._upper)
+            bounds[i] = (param.lower_vectorized, param.upper_vectorized)  # type: ignore
         elif isinstance(param, BetaIntegerHyperparameter):
             if can_be_inactive:
                 raise ValueError(
                     "Inactive parameters not supported for Beta and Normal Hyperparameters"
                 )
 
-            bounds[i] = (param.bfhp._lower, param.bfhp._upper)
+            bounds[i] = (param.lower_vectorized, param.upper_vectorized)  # type: ignore
         elif not isinstance(
             param,
             (

deepcave/evaluators/fanova.py

@@ -50,7 +50,7 @@ def __init__(self, run: AbstractRun):
         self.run = run
         self.cs = run.configspace
         self.hps = self.cs.get_hyperparameters()
-        self.hp_names = self.cs.get_hyperparameter_names()
+        self.hp_names = list(self.cs.keys())
         self.logger = get_logger(self.__class__.__name__)
 
     def calculate(

deepcave/evaluators/footprint.py

@@ -131,7 +131,7 @@ def calculate(
         data = self.run.get_encoded_data(
             objective, budget, statuses=Status.SUCCESS, specific=False, include_config_ids=True
         )
-        hp_names = self.run.configspace.get_hyperparameter_names()
+        hp_names = list(self.run.configspace.keys())
 
         # Make numpy arrays
         X = data[hp_names].to_numpy()

deepcave/evaluators/lpi.py

@@ -14,7 +14,11 @@
 from ConfigSpace import Configuration
 from ConfigSpace.c_util import change_hp_value, check_forbidden
 from ConfigSpace.exceptions import ForbiddenValueError
-from ConfigSpace.hyperparameters import CategoricalHyperparameter
+from ConfigSpace.hyperparameters import (
+    CategoricalHyperparameter,
+    NumericalHyperparameter,
+)
+from ConfigSpace.types import Array, f64
 from ConfigSpace.util import impute_inactive_values
 
 from deepcave.constants import COMBINED_COST_NAME
@@ -157,7 +161,9 @@ def calculate(
 
                 # Create the neighbor-Configuration object
                 new_array = self.incumbent_array.copy()
-                new_array = change_hp_value(self.cs, new_array, hp_name, unit_neighbor, hp_idx)
+                new_array = change_hp_value(
+                    self.cs, new_array, hp_name, unit_neighbor, self.cs.index_of[hp_name]
+                )
                 new_config = impute_inactive_values(Configuration(self.cs, vector=new_array))
 
                 # Get the leaf values
@@ -296,12 +302,15 @@ def _get_neighborhood(self) -> Dict[str, List[Union[np.ndarray, List[np.ndarray]
             hp_neighborhood = []
             checked_neighbors = []  # On unit cube
             checked_neighbors_non_unit_cube = []  # Not on unit cube
-            hp = self.cs.get_hyperparameter(hp_name)
+            hp = self.cs[hp_name]
             num_neighbors = hp.get_num_neighbors(self.incumbent[hp_name])
 
+            neighbors: Union[List[Union[f64]], Array[Union[f64]]]
+
             if num_neighbors == 0:
                 continue
             elif np.isinf(num_neighbors):
+                assert isinstance(hp, NumericalHyperparameter)
                 if hp.log:
                     base = np.e
                     log_lower = np.log(hp.lower) / np.log(base)
@@ -315,7 +324,7 @@ def _get_neighborhood(self) -> Dict[str, List[Union[np.ndarray, List[np.ndarray]
                     )
                 else:
                     neighbors_range = np.linspace(hp.lower, hp.upper, self.continous_neighbors)
-                neighbors = list(map(lambda x: hp._inverse_transform(x), neighbors_range))
+                neighbors = list(map(lambda x: hp.to_vector(x), neighbors_range))
             else:
                 neighbors = hp.get_neighbors(self.incumbent_array[hp_idx], self.rs)
 
@@ -329,7 +338,7 @@ def _get_neighborhood(self) -> Dict[str, List[Union[np.ndarray, List[np.ndarray]
                 try:
                     new_config = Configuration(self.cs, vector=new_array)
                     hp_neighborhood.append(new_config)
-                    new_config.is_valid_configuration()
+                    new_config.check_valid_configuration()
                     check_forbidden(self.cs.forbidden_clauses, new_array)
 
                     checked_neighbors.append(neighbor)
@@ -340,7 +349,7 @@ def _get_neighborhood(self) -> Dict[str, List[Union[np.ndarray, List[np.ndarray]
             sort_idx = list(
                 map(lambda x: x[0], sorted(enumerate(checked_neighbors), key=lambda y: y[1]))
             )
-            if isinstance(self.cs.get_hyperparameter(hp_name), CategoricalHyperparameter):
+            if isinstance(self.cs[hp_name], CategoricalHyperparameter):
                 checked_neighbors_non_unit_cube_categorical = list(
                     np.array(checked_neighbors_non_unit_cube)[sort_idx]
                 )

deepcave/plugins/hyperparameter/importances.py

@@ -224,7 +224,7 @@ def load_dependency_inputs(self, run, _: Any, inputs: Dict[str, Any]) -> Dict[st
         budget_options = get_checklist_options(budgets, budget_ids)
         budget_value = inputs["budget_ids"]["value"]
 
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
         hp_options = get_checklist_options(hp_names)
         hp_value = inputs["hyperparameter_names"]["value"]
         n_hps = inputs["n_hps"]["value"]
@@ -315,8 +315,8 @@ def process(run: AbstractRun, inputs: Dict[str, Any]) -> Dict[str, Any]:
             configspace_wo_const = ConfigurationSpace()
             for k in hp_dict_wo_const.keys():
                 configspace_wo_const.add_hyperparameter(hp_dict_wo_const[k])
-            configspace_wo_const.add_conditions(run.configspace.get_conditions())
-            configspace_wo_const.add_forbidden_clauses(run.configspace.get_forbiddens())
+            configspace_wo_const.add(run.configspace.conditions)
+            configspace_wo_const.add(run.configspace.forbidden_clauses)
             run.configspace = configspace_wo_const
 
             configs_wo_const = []
@@ -326,7 +326,7 @@ def process(run: AbstractRun, inputs: Dict[str, Any]) -> Dict[str, Any]:
                 )
             run.configs = dict(enumerate(configs_wo_const))
 
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
         budgets = run.get_budgets(include_combined=True)
 
         evaluator: Optional[Union[LocalEvaluator, GlobalEvaluator]] = None

deepcave/plugins/hyperparameter/pdp.py

@@ -231,7 +231,7 @@ def load_dependency_inputs(self, run, previous_inputs, inputs) -> Dict[str, Any]
         budget_ids = run.get_budget_ids()
         budget_options = get_checklist_options(budgets, budget_ids)
 
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
 
         # Get selected values
         objective_value = inputs["objective_id"]["value"]
@@ -288,7 +288,7 @@ def process(run, inputs) -> Dict[str, Any]:  # type: ignore
             If the objective is None.
         """
         # Surrogate
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
         objective = run.get_objective(inputs["objective_id"])
         budget = run.get_budget(inputs["budget_id"])
         hp1 = inputs["hyperparameter_name_1"]
@@ -404,14 +404,14 @@ def get_pdp_figure(  # type: ignore
         # Parse inputs
         hp1_name = inputs["hyperparameter_name_1"]
         hp1_idx = run.configspace.get_idx_by_hyperparameter_name(hp1_name)
-        hp1 = run.configspace.get_hyperparameter(hp1_name)
+        hp1 = run.configspace[hp1_name]
 
         hp2_name = inputs["hyperparameter_name_2"]
         hp2_idx = None
         hp2 = None
         if hp2_name is not None and hp2_name != "":
             hp2_idx = run.configspace.get_idx_by_hyperparameter_name(hp2_name)
-            hp2 = run.configspace.get_hyperparameter(hp2_name)
+            hp2 = run.configspace[hp2_name]
 
         objective = run.get_objective(inputs["objective_id"])
         objective_name = objective.name
@@ -425,7 +425,7 @@ def get_pdp_figure(  # type: ignore
         y_ice = np.asarray(outputs["y_ice"])
 
         traces = []
-        if hp2_idx is None:  # 1D
+        if hp2 is None:  # 1D
             # Add ICE curves
             if show_ice:
                 for x_, y_ in zip(x_ice, y_ice):

deepcave/plugins/hyperparameter/symbolic_explanations.py

@@ -346,7 +346,7 @@ def process(run, inputs) -> Dict[str, Any]:  # type: ignore
         RuntimeError
             If the objective is None.
         """
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
         objective = run.get_objective(inputs["objective_id"])
         budget = run.get_budget(inputs["budget_id"])
         hp1 = inputs["hyperparameter_name_1"]
@@ -533,18 +533,18 @@ def load_outputs(run, inputs, outputs) -> List[go.Figure]:  # type: ignore
         """
         hp1_name = inputs["hyperparameter_name_1"]
         hp1_idx = run.configspace.get_idx_by_hyperparameter_name(hp1_name)
-        hp1 = run.configspace.get_hyperparameter(hp1_name)
+        hp1 = run.configspace[hp1_name]
         selected_hyperparameters = [hp1]
 
         hp2_name = inputs["hyperparameter_name_2"]
         hp2_idx = None
         hp2 = None
         if hp2_name is not None and hp2_name != "":
             hp2_idx = run.configspace.get_idx_by_hyperparameter_name(hp2_name)
-            hp2 = run.configspace.get_hyperparameter(hp2_name)
+            hp2 = run.configspace[hp2_name]
             selected_hyperparameters += [hp2]
 
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
         objective = run.get_objective(inputs["objective_id"])
         objective_name = objective.name
 

deepcave/plugins/objective/configuration_cube.py

@@ -195,7 +195,7 @@ def load_dependency_inputs(self, run, _, inputs) -> Dict[str, Any]:  # type: ign
         budget_value = inputs["budget_id"]["value"]
 
         # Prepare others
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
 
         # Get selected values
         n_configs_value = inputs["n_configs"]["value"]
@@ -348,7 +348,7 @@ def load_outputs(run, inputs, outputs) -> go.Figure:  # type: ignore
         layout_kwargs = {}
         if n_configs > 0 and len(hp_names) > 0:
             for i, (hp_name, axis_name) in enumerate(zip(hp_names, ["xaxis", "yaxis", "zaxis"])):
-                hp = run.configspace.get_hyperparameter(hp_name)
+                hp = run.configspace[hp_name]
                 values = df[hp_name].values.tolist()
 
                 tickvals, ticktext = get_hyperparameter_ticks(hp, ticks=4, include_nan=True)

deepcave/plugins/objective/parallel_coordinates.py

@@ -220,7 +220,7 @@ def load_dependency_inputs(self, run, _, inputs) -> Dict[str, Any]:  # type: ign
 
         # Prepare others
         n_hps = inputs["n_hps"]["value"]
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
 
         if inputs["show_important_only"]["value"] == "true":
             hp_options = []
@@ -398,7 +398,7 @@ def load_outputs(run, inputs, outputs) -> go.Figure:  # type: ignore
             data[hp_name]["label"] = hp_name
             data[hp_name]["range"] = VALUE_RANGE
 
-            hp = run.configspace.get_hyperparameter(hp_name)
+            hp = run.configspace[hp_name]
             tickvals, ticktext = get_hyperparameter_ticks(hp, ticks=4, include_nan=True)
 
             data[hp_name]["tickvals"] = tickvals

deepcave/plugins/summary/configurations.py

@@ -264,7 +264,7 @@ def process(run, inputs) -> Dict[str, Any]:  # type: ignore
             # And add it to the lists
             X.append(x)
 
-        columns = run.configspace.get_hyperparameter_names()
+        columns = list(run.configspace.keys())
         columns += ["highlighted"]
 
         cs_df = pd.DataFrame(data=X, columns=columns)
@@ -449,7 +449,7 @@ def _get_configspace_figure(
         df = deserialize(outputs["cs_df"], dtype=pd.DataFrame)
 
         highlighted = df["highlighted"].values
-        hp_names = run.configspace.get_hyperparameter_names()
+        hp_names = list(run.configspace.keys())
 
         # Get highlighted column
         highlighted_df = df[df["highlighted"] == 1]
@@ -460,7 +460,7 @@ def _get_configspace_figure(
             data[hp_name]["label"] = hp_name
             data[hp_name]["range"] = VALUE_RANGE
 
-            hp = run.configspace.get_hyperparameter(hp_name)
+            hp = run.configspace[hp_name]
             tickvals, ticktext = get_hyperparameter_ticks(
                 hp, additional_values=highlighted_df[hp_name].values, ticks=4, include_nan=True
             )