diff --git a/flood_forecast/evaluator.py b/flood_forecast/evaluator.py
index c0c7f9d14..b90f7273b 100644
--- a/flood_forecast/evaluator.py
+++ b/flood_forecast/evaluator.py
@@ -333,7 +333,27 @@ def infer_on_torch_model(
 
 def handle_evaluation_series_loader(csv_series_id_loader: SeriesIDTestLoader, model, device,
                                     hours_to_forecast: int, datetime_start):
-    pass
+    data = csv_series_id_loader.get_from_start_date_all(datetime_start)
+    for i in range(0, len(data)):
+        history, df_train_and_test, forecast_start_idx = data[i]
+        print(history)
+        print(df_train_and_test)
+        print(forecast_start_idx)
+        """
+        end_tensor = generate_predictions(
+            model,
+            df_train_and_test,
+            csv_series_id_loader,
+            history,
+            device,
+            forecast_start_idx,
+            model.params["dataset_params"]["forecast_length"],
+            hours_to_forecast,
+            decoder_params=None,
+            multi_params=1
+        )
+        print(end_tensor)"""
+    return
 
 
 def handle_ci_multi(prediction_samples: torch.Tensor, csv_test_loader: CSVTestLoader, multi_params: int,
diff --git a/tests/test_series_id.py b/tests/test_series_id.py
index 555efe83b..36380f96d 100644
--- a/tests/test_series_id.py
+++ b/tests/test_series_id.py
@@ -51,7 +51,7 @@ def __init__(self, model):
 
     def test_series_test_loader(self):
         loader_ds1 = SeriesIDTestLoader("PLANT_ID", self.dataset_params, "shit")
-        self.assertEqual(loader_ds1.get_from_start_date_all(datetime(2020, 8, 1))[0][0].shape[0], 20)
+        self.assertEqual(loader_ds1.get_from_start_date_all(datetime(2020, 7, 6))[0][0].shape[0], 20)
         # historical_rows, all_rows_orig, targ_idx = loader_ds1.get_from_start_date_all(datetime(2020, 8, 1))[0]
         # self.assertEqual(historical_rows.shape[0], 20)
         # self.assertEqual(historical_rows.shape[1], 3)