Merge branch 'master' into feat/onnx_support

CHANGELOG.md

@@ -12,6 +12,9 @@ but cannot always guarantee backwards compatibility. Changes that may **break co
 **Improved**
 
 - Added ONNX support for torch-based models with method `TorchForecastingModel.to_onnx()`. Check out [this example](https://unit8co.github.io/darts/userguide/gpu_and_tpu_usage.html#exporting-model-to-onnx-format-for-inference) from the user guide on how to export and load a model for inference. [#2620](https://github.com/unit8co/darts/pull/2620) by [Antoine Madrona](https://github.com/madtoinou)
+- Made method `ForecastingModel.untrained_model()` public. Use this method to get a new (untrained) model instance created with the same parameters. [#2684](https://github.com/unit8co/darts/pull/2684) by [Timon Erhart](https://github.com/turbotimon)
+
+**Fixed**
 
 **Dependencies**
 

darts/models/forecasting/forecasting_model.py

@@ -2601,7 +2601,7 @@ def _extract_model_creation_params(self):
         return model_params
 
     def untrained_model(self):
-        """Returns a new (untrained) model instance create with the same parameters."""
+        """Returns a new (untrained) model instance created with the same parameters."""
         return self.__class__(**copy.deepcopy(self.model_params))
 
     @property

docs/source/conf.py

@@ -54,7 +54,7 @@
     + "PastCovariatesTorchModel,FutureCovariatesTorchModel,DualCovariatesTorchModel,MixedCovariatesTorchModel,"
     + "SplitCovariatesTorchModel,"
     + "min_train_series_length,"
-    + "untrained_model,first_prediction_index,future_covariate_series,past_covariate_series,"
+    + "first_prediction_index,future_covariate_series,past_covariate_series,"
     + "initialize_encoders,register_datapipe_as_function,register_function,functions,"
     + "SplitTimeSeriesSequence,randint,AnomalyModel",
 }