Turnoff deep serialization (#160)

* Set deep to False in autoestimator dict_serialization.

* Set deep to False in preparestep dict_serialization.

* Use default dict_serialization method in SmartTransformer.

* Set deep to False in columnsharer dict_serialization

* Set deep to False in Preparer dict_serialization

* Use default dict_serialization in auto_estimator

foreshadow/columnsharer.py

@@ -44,7 +44,7 @@ def __init__(self, *args, **kwargs):
             lambda: False, acceptable_keys
         )
 
-    def dict_serialize(self, deep=True):
+    def dict_serialize(self, deep=False):
         """Serialize the init parameters (dictionary form) of a columnsharer.
 
         Args:

foreshadow/estimators/auto.py

@@ -41,9 +41,6 @@ def __init__(
         self.estimator_class = None
         self.estimator = None
 
-    def dict_serialize(self, deep=True):  # noqa
-        return super().dict_serialize(deep=False)
-
     @property
     def problem_type(self):
         """Type of machine learning problem.

foreshadow/preparer.py

@@ -125,7 +125,7 @@ def _get_params(self, attr, deep=True):
         # adding steps to the get_params()
         return out
 
-    def dict_serialize(self, deep=True):
+    def dict_serialize(self, deep=False):
         """Serialize the data preparer.
 
         Args:

foreshadow/smart/smart.py

@@ -77,10 +77,6 @@ def __init__(
         self.transformer = transformer
         self.check_wrapped = check_wrapped
 
-    def dict_serialize(self, deep=True):  # noqa
-        serialized = super().dict_serialize(deep=False)
-        return serialized
-
     @property
     def transformer(self):
         """Get the selected transformer from the SmartTransformer.

foreshadow/steps/preparerstep.py

@@ -291,7 +291,7 @@ def configure_column_sharer(self, column_sharer):
         super().configure_column_sharer(column_sharer)
         self._parallel_process.configure_column_sharer(column_sharer)
 
-    def dict_serialize(self, deep=True):
+    def dict_serialize(self, deep=False):
         """Serialize the preparestep.
 
         It renames transformer_list to transformation_by_column_group.