Merge branch 'lukas_issue343_bug_fix-bugs-caused-by-model-name-refac-and-tf-update' into 'develop'

Resolve "fix bugs caused by model name refac and tf update"

See merge request !366

mlair/model_modules/abstract_model_class.py

@@ -38,9 +38,9 @@ class AbstractModelClass(ABC):
         self._input_shape = input_shape
         self._output_shape = self.__extract_from_tuple(output_shape)
 
-    def load_model(self, name: str, compile: bool = False):
+    def load_model(self, name: str, compile: bool = False) -> None:
         hist = self.model.history
-        self.model = keras.models.load_model(name)
+        self.model.load_weights(name)
         self.model.history = hist
         if compile is True:
             self.model.compile(**self.compile_options)

mlair/run_modules/post_processing.py

@@ -421,7 +421,7 @@ class PostProcessing(RunEnvironment):
         """Return model name without path information."""
         return self.data_store.get("model_name", "model").rsplit("/", 1)[1].split(".", 1)[0]
 
-    def _load_model(self) -> keras.models:
+    def _load_model(self) -> AbstractModelClass:
         """
         Load NN model either from data store or from local path.
 
@@ -907,10 +907,11 @@ class PostProcessing(RunEnvironment):
         errors = {}
         for station in all_stations:
             external_data = self._get_external_data(station, path)  # test data
-            external_data.coords[self.model_type_dim] = [{self.forecast_indicator: self.model_display_name}.get(n, n)
-                                                         for n in external_data.coords[self.model_type_dim].values]
+
             # test errors
             if external_data is not None:
+                external_data.coords[self.model_type_dim] = [{self.forecast_indicator: self.model_display_name}.get(n, n)
+                                                              for n in external_data.coords[self.model_type_dim].values]
                 model_type_list = external_data.coords[self.model_type_dim].values.tolist()
                 for model_type in remove_items(model_type_list, self.observation_indicator):
                     if model_type not in errors.keys():