Fix TypeError in pipeline run initialization by detecting skopt spaces

- Added detection logic for `skopt` space objects (`Real`, `Integer`, `Categorical`) in `ml_grid/pipeline/main.py`.
- Updated parameter grid size calculation to use `calculate_combinations` instead of `ParameterGrid` when Bayesian parameter spaces are detected, even if `bayessearch` is globally False.
- Prevents `TypeError` when `ParameterGrid` encounters non-iterable `skopt` objects during pipeline initialization.

Author: SamoraHunter

ml_grid/pipeline/main.py

@@ -7,6 +7,7 @@
 
 import numpy as np
 from sklearn.model_selection import ParameterGrid
+from skopt.space import Categorical, Integer, Real
 
 from ml_grid.pipeline import grid_search_cross_validate
 from ml_grid.pipeline.data import pipe
@@ -181,17 +182,27 @@ def __init__(self, local_param_dict: Dict[str, Any], **kwargs):
 
         for elem in self.model_class_list:
 
-            if not self.global_params.bayessearch:
-                # ParameterGrid can now be called directly, as the model class
-                # provides a grid-search-compatible parameter space.
+            # Check if the parameter space contains skopt objects
+            is_bayes_space = False
+            space_to_check = elem.parameter_space
+            if isinstance(space_to_check, list) and space_to_check:
+                space_to_check = space_to_check[0]  # Check the first dict
+
+            if isinstance(space_to_check, dict):
+                if any(
+                    isinstance(v, (Real, Integer, Categorical))
+                    for v in space_to_check.values()
+                ):
+                    is_bayes_space = True
+
+            if not self.global_params.bayessearch and not is_bayes_space:
+                # This is a true grid search space
                 pg = ParameterGrid(elem.parameter_space)
                 pg = len(pg)
             else:
-
+                # This handles both explicit bayessearch=True and mismatched grid spaces
                 pg = calculate_combinations(elem.parameter_space, steps=10)
 
-            # pg = ParameterGrid(elem.parameter_space)
-
             self.pg_list.append(pg)
 
             if self.verbose >= 1: