small changes

Author: govarsha

ads/opctl/operator/lowcode/forecast/model/automlx.py

@@ -175,10 +175,8 @@ def _build_model(self) -> pd.DataFrame:
                 "time_series_period": model.time_series_period,
                 "min_class_instances": model.min_class_instances,
                 "max_tuning_trials": model.max_tuning_trials,
-                "contamination": model_kwargs_cleaned.get("contamination", 0.01),
                 "selected_model": model.selected_model_,
                 "selected_model_params": model.selected_model_params_,
-                "time_budget": time_budget,
             }
 
         logger.debug("===========Forecast Generated===========")

ads/opctl/operator/lowcode/forecast/model/base_model.py

@@ -547,14 +547,7 @@ def _save_report(
 
         # model pickle
         if self.spec.generate_model_pickle:
-            utils.write_pkl(
-                obj=self.models,
-                filename="model.pkl",
-                output_dir=output_dir,
-                storage_options=storage_options,
-            )
-
-        self._save_model_specific_files(output_dir, storage_options)
+            self._save_model(output_dir, storage_options)
 
         logger.info(
             f"The outputs have been successfully "
@@ -595,11 +588,14 @@ def _load_model(self):
         except:
             logger.info("model.pkl is not present")
 
-    def _save_model_specific_files(self, output_dir, storage_options):
-        """
-        The method that needs to be implemented on the particular model level
-        """
-        pass
+    def _save_model(self, output_dir, storage_options):
+        utils.write_pkl(
+            obj=self.models,
+            filename="model.pkl",
+            output_dir=output_dir,
+            storage_options=storage_options,
+        )
+
 
 
     @runtime_dependency(

ads/opctl/operator/lowcode/forecast/model/neuralprophet.py

@@ -323,14 +323,19 @@ def objective(trial):
 
         return output_col
 
-    def _save_model_specific_files(self, output_dir, storage_options):
-        if self.spec.generate_model_pickle and self.trainers is not None:
-            utils.write_pkl(
-                obj=self.trainers,
-                filename="trainer.pkl",
-                output_dir=output_dir,
-                storage_options=storage_options,
-            )
+    def _save_model(self, output_dir, storage_options):
+        utils.write_pkl(
+            obj=self.models,
+            filename="model.pkl",
+            output_dir=output_dir,
+            storage_options=storage_options,
+        )
+        utils.write_pkl(
+            obj=self.trainers,
+            filename="trainer.pkl",
+            output_dir=output_dir,
+            storage_options=storage_options,
+        )
 
     def _generate_report(self):
         import datapane as dp