clean up and fixes

Author: prasankh

ads/opctl/operator/lowcode/forecast/whatifserve/deployment_manager.py

@@ -12,6 +12,7 @@
 import pandas as pd
 from joblib import dump
 
+from ads.opctl import logger
 from ads.common.model_export_util import prepare_generic_model
 from ads.opctl.operator.lowcode.common.utils import write_data, call_pandas_fsspec
 
@@ -22,7 +23,6 @@
 class ModelDeploymentManager:
     def __init__(self, spec: ForecastOperatorSpec, additional_data: AdditionalData, previous_model_version=None):
         self.spec = spec
-        # self.model_path = spec.output_directory.url
         self.model_name = spec.model
         self.horizon = spec.horizon
         self.additional_data = additional_data.get_dict_by_series()
@@ -51,7 +51,7 @@ def _satiny_test(self):
             additional_data_uri = "additional_data_uri"
             input_data = {additional_data_uri: temp_file.name}
             prediction_test = predict(input_data, _)
-            print(f"prediction test completed with result :{prediction_test}")
+            logger.info(f"prediction test completed with result :{prediction_test}")
 
     def _copy_score_file(self):
         """
@@ -62,9 +62,9 @@ def _copy_score_file(self):
             score_file = os.path.join(current_dir, "score.py")
             destination_file = os.path.join(self.path_to_artifact, os.path.basename(score_file))
             shutil.copy2(score_file, destination_file)
-            print(f"score.py copied successfully to {self.path_to_artifact}")
+            logger.info(f"score.py copied successfully to {self.path_to_artifact}")
         except Exception as e:
-            print(f"Error copying file: {e}")
+            logger.warn(f"Error copying file: {e}")
             raise e
 
     def save_to_catalog(self):
@@ -82,7 +82,7 @@ def save_to_catalog(self):
 
         self._copy_score_file()
         self._satiny_test()
-        
+
         if isinstance(self.model_obj, dict):
             series = self.model_obj.keys()
         else:
@@ -96,7 +96,7 @@ def save_to_catalog(self):
             catalog_id = catalog_entry.id
 
 
-        print(f"Saved {self.model_name} version-v{self.model_version} to model catalog"
+        logger.info(f"Saved {self.model_name} version-v{self.model_version} to model catalog"
               f" with catalog id : {catalog_id}")
 
         catalog_mapping = {"catalog_id": catalog_id, "series": list(series)}

ads/opctl/operator/lowcode/forecast/whatifserve/score.py

@@ -135,21 +135,22 @@ def post_inference(yhat):
 def get_forecast(future_df, series_id, model_object, date_col, target_column, target_cat_col, horizon):
     date_col_name = date_col["name"]
     date_col_format = date_col["format"]
+    future_df[target_cat_col] = future_df[target_cat_col].astype("str")
     future_df[date_col_name] = pd.to_datetime(
         future_df[date_col_name], format=date_col_format
     )
     if isinstance(model_object, AutoTS):
-        full_data_indexed = future_df
+        series_id_col = "Series"
+        full_data_indexed = future_df.rename(columns={target_cat_col: series_id_col})
         additional_regressors = list(
-            set(full_data_indexed.columns) - {target_column, target_cat_col, date_col_name}
+            set(full_data_indexed.columns) - {target_column, series_id_col, date_col_name}
         )
-        future_regressor = full_data_indexed.reset_index().pivot(
+        future_reg = full_data_indexed.reset_index().pivot(
             index=date_col_name,
-            columns=target_cat_col,
+            columns=series_id_col,
             values=additional_regressors,
         )
-        regr_fcst = future_regressor
-        pred_obj = model_object.predict(future_regressor=regr_fcst)
+        pred_obj = model_object.predict(future_regressor=future_reg)
         return pred_obj.forecast[series_id].tolist()
     elif series_id in model_object and isinstance(model_object[series_id], Prophet):
         model = model_object[series_id]