moving logic from pre and post processes to predict

python/sklearnserver/sklearnserver/model.py

@@ -15,18 +15,19 @@ def load(self):
         self.ready = True
 
     def preprocess(self, inputs):
+        return inputs
+
+    def postprocess(self, outputs):
+        return outputs
+
+    def predict(self, inputs):
         try:
-            return np.array(inputs)
+            inputs = np.array(inputs)
         except Exception as e:
             raise Exception(
                 "Failed to initialize NumPy array from inputs: %s, %s" % (e, inputs))
-
-    def postprocess(self, outputs):
-        return outputs.tolist()
-
-    def predict(self, inputs):
         try:
-            result = self._joblib.predict(inputs)
+            result = self._joblib.predict(inputs).tolist()
             return result
         except Exception as e:
             raise Exception("Failed to predict %s" % e)