fixed code documentation issued

SKSurrogate/aml.py

@@ -137,6 +137,11 @@ def Generate(self, l):
     Integer = lambda a, b: None
     Categorical = lambda a: None
     HDReal = lambda a, b: None
+except ImportError:
+    Real = lambda a, b: None
+    Integer = lambda a, b: None
+    Categorical = lambda a: None
+    HDReal = lambda a, b: None
 
 default_config = {
     # Classifiers
@@ -461,8 +466,7 @@ def _cast(self, n, X, y):
         :param y: Observed values
         :return: None
         """
-        from .structsearch import SurrogateRandomCV, BoxSample, CompactSample
-        from importlib import import_module
+        from .structsearch import BoxSample, CompactSample
         if self.couldBfirst == []:
             from sklearn.pipeline import Pipeline
         else:

SKSurrogate/structsearch.py

@@ -632,7 +632,7 @@ class SurrogateRandomCV(BaseSearchCV):
 
     :param estimator: estimator object. A object of that type is instantiated for each search point. This object is
         assumed to implement the scikit-learn estimator api. Either estimator needs to provide a ``score`` function,
-            or ``scoring`` must be passed.
+        or ``scoring`` must be passed.
     :param params: dict Dictionary with parameters names (string) as keys and domains as lists of parameter ranges
         to try. Domains are either lists of categorical (string) values or 2 element lists specifying a min and max
         for integer or float parameters