refactor: replace selt.ts with ts, remove redundant checks of self.ts

etna/pipeline/base.py

@@ -325,10 +325,7 @@ def _add_forecast_borders(
         self, ts: TSDataset, backtest_forecasts: pd.DataFrame, quantiles: Sequence[float], predictions: TSDataset
     ) -> None:
         """Estimate prediction intervals and add to the forecasts."""
-        if self.ts is None:
-            raise ValueError("Pipeline is not fitted!")
-
-        backtest_forecasts = TSDataset(df=backtest_forecasts, freq=self.ts.freq)
+        backtest_forecasts = TSDataset(df=backtest_forecasts, freq=ts.freq)
         residuals = (
             backtest_forecasts.loc[:, pd.IndexSlice[:, "target"]]
             - ts[backtest_forecasts.index.min() : backtest_forecasts.index.max(), :, "target"]

etna/pipeline/hierarchical_pipeline.py

@@ -116,7 +116,7 @@ def raw_forecast(
             freq=forecast.freq,
             df_exog=forecast.df_exog,
             known_future=forecast.known_future,
-            hierarchical_structure=self.ts.hierarchical_structure,  # type: ignore
+            hierarchical_structure=ts.hierarchical_structure,  # type: ignore
         )
         return hierarchical_forecast
 

tests/test_pipeline/test_hierarchical_pipeline.py

@@ -1,5 +1,4 @@
 import pathlib
-from copy import deepcopy
 from unittest.mock import Mock
 from unittest.mock import patch
 
@@ -23,7 +22,8 @@
 from etna.transforms import LinearTrendTransform
 from etna.transforms import MeanTransform
 from tests.test_pipeline.utils import assert_pipeline_equals_loaded_original
-from tests.test_pipeline.utils import assert_pipeline_forecasts_given_ts_with_prediction_intervals, assert_pipeline_forecasts_given_ts
+from tests.test_pipeline.utils import assert_pipeline_forecasts_given_ts
+from tests.test_pipeline.utils import assert_pipeline_forecasts_given_ts_with_prediction_intervals
 from tests.utils import to_be_fixed