Bug fixed: autosklearn

pkg/meta.yaml

@@ -3,7 +3,7 @@
 
 package:
   name: pyepo
-  version: 0.4.3
+  version: 0.4.4
 
 source:
   path: ./

pkg/pyepo/twostage/autosklearnpred.py

@@ -19,44 +19,6 @@
 
 from pyepo.metric import makeAutoSkScorer
 
-class NoPreprocessing(AutoSklearnPreprocessingAlgorithm):
-    """
-    This is class of NoPreprocessing component for auto-sklearn
-    """
-    def __init__(self, **kwargs):
-        """
-        This preprocessors does not change the data
-        """
-        # Some internal checks makes sure parameters are set
-        for key, val in kwargs.items():
-            setattr(self, key, val)
-
-    def fit(self, X, Y=None):
-        return self
-
-    def transform(self, X):
-        return X
-
-    @staticmethod
-    def get_properties(dataset_properties=None):
-        return {
-            "shortname": "NoPreprocessing",
-            "name": "NoPreprocessing",
-            "handles_regression": True,
-            "handles_classification": True,
-            "handles_multiclass": True,
-            "handles_multilabel": True,
-            "handles_multioutput": True,
-            "is_deterministic": True,
-            "input": (SPARSE, DENSE, UNSIGNED_DATA),
-            "output": (INPUT,)
-        }
-
-    @staticmethod
-    def get_hyperparameter_search_space(dataset_properties=None):
-        return ConfigurationSpace()  # Return an empty configuration as there is None
-
-
 def autoSklearnPred(optmodel, seed, timelimit, metric="mse"):
     """
     Two-stage prediction and optimization with auto-sklearn.
@@ -70,6 +32,42 @@ def autoSklearnPred(optmodel, seed, timelimit, metric="mse"):
     # error
     if not _HAS_AUTO:
         raise ImportError("Autosklearn is not installed. Please install autosklearn to use this feature.")
+    class NoPreprocessing(AutoSklearnPreprocessingAlgorithm):
+        """
+        This is class of NoPreprocessing component for auto-sklearn
+        """
+        def __init__(self, **kwargs):
+            """
+            This preprocessors does not change the data
+            """
+            # Some internal checks makes sure parameters are set
+            for key, val in kwargs.items():
+                setattr(self, key, val)
+
+        def fit(self, X, Y=None):
+            return self
+
+        def transform(self, X):
+            return X
+
+        @staticmethod
+        def get_properties(dataset_properties=None):
+            return {
+                "shortname": "NoPreprocessing",
+                "name": "NoPreprocessing",
+                "handles_regression": True,
+                "handles_classification": True,
+                "handles_multiclass": True,
+                "handles_multilabel": True,
+                "handles_multioutput": True,
+                "is_deterministic": True,
+                "input": (SPARSE, DENSE, UNSIGNED_DATA),
+                "output": (INPUT,)
+            }
+
+        @staticmethod
+        def get_hyperparameter_search_space(dataset_properties=None):
+            return ConfigurationSpace()  # Return an empty configuration as there is None
     # add NoPreprocessing component to auto-sklearn.
     data_preprocessing.add_preprocessor(NoPreprocessing)
     # get metrics

pkg/setup.py

@@ -17,7 +17,7 @@
     long_description=long_description,
     long_description_content_type="text/markdown",
     # version
-    version = "0.4.3",
+    version = "0.4.4",
     # Github repo
     url = "https://github.com/khalil-research/PyEPO",
     # author name