modification to work with latest sklearn

evolutionary_search/cv.py

@@ -3,16 +3,41 @@
 import os
 import warnings
 
+from collections.abc import Sequence
 import numpy as np
 import random
 from deap import base, creator, tools, algorithms
 from collections import defaultdict
 from sklearn.base import clone, is_classifier
 from sklearn.model_selection._validation import _fit_and_score
-from sklearn.model_selection._search import BaseSearchCV, check_cv, _check_param_grid
+from sklearn.model_selection._search import BaseSearchCV, check_cv
 from sklearn.metrics import check_scoring
 from sklearn.utils.validation import _num_samples, indexable
 
+#This code is obtained from the older version of sklearn
+def _check_param_grid(param_grid):
+    if hasattr(param_grid, "items"):
+        param_grid = [param_grid]
+
+    for p in param_grid:
+        for name, v in p.items():
+            if isinstance(v, np.ndarray) and v.ndim > 1:
+                raise ValueError("Parameter array should be one-dimensional.")
+
+            if isinstance(v, str) or not isinstance(v, (np.ndarray, Sequence)):
+                raise ValueError(
+                    "Parameter grid for parameter ({0}) needs to"
+                    " be a list or numpy array, but got ({1})."
+                    " Single values need to be wrapped in a list"
+                    " with one element.".format(name, type(v))
+                )
+
+            if len(v) == 0:
+                raise ValueError(
+                    "Parameter values for parameter ({0}) need "
+                    "to be a non-empty sequence.".format(name)
+                )
+
 
 def enum(**enums):
     return type("Enum", (), enums)