Make in-sample predictions of SARIMAXModel non-dynamic in all cases

CHANGELOG.md

@@ -43,7 +43,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - 
 - 
 - 
-- 
+- Make in-sample predictions of SARIMAXModel non-dynamic in all cases ([#812](https://github.com/tinkoff-ai/etna/pull/812))
 - Teach BATS/TBATS to work with in-sample, out-sample predictions correctly ([#806](https://github.com/tinkoff-ai/etna/pull/806))
 - 
 - Github actions cache issue with poetry update ([#778](https://github.com/tinkoff-ai/etna/pull/778))

etna/models/sarimax.py

@@ -274,7 +274,7 @@ def predict(self, df: pd.DataFrame, prediction_interval: bool, quantiles: Sequen
                 y_pred[f"mean_{quantile:.4g}"] = series
         else:
             forecast = self._result.get_prediction(
-                start=df["timestamp"].min(), end=df["timestamp"].max(), dynamic=True, exog=exog_future
+                start=df["timestamp"].min(), end=df["timestamp"].max(), dynamic=False, exog=exog_future
             )
             y_pred = forecast.predicted_mean
             y_pred.name = "mean"

tests/test_models/test_inference.py

@@ -418,6 +418,7 @@ def test_forecast_out_sample_suffix_failed(model, transforms, example_tsds):
         (ElasticPerSegmentModel(), [LagTransform(in_column="target", lags=[5, 6])]),
         (ElasticMultiSegmentModel(), [LagTransform(in_column="target", lags=[5, 6])]),
         (ProphetModel(), []),
+        (SARIMAXModel(), []),
         (HoltModel(), []),
         (HoltWintersModel(), []),
         (SimpleExpSmoothingModel(), []),
@@ -431,7 +432,6 @@ def test_forecast_mixed_in_out_sample(model, transforms, example_tsds):
 @pytest.mark.parametrize(
     "model, transforms",
     [
-        (SARIMAXModel(), []),
         (AutoARIMAModel(), []),
         (
             DeepARModel(max_epochs=5, learning_rate=[0.01]),