🐛 Removed match case statements to support python 3.9

RoyalHaskoningDHV · Dec 19, 2024 · 0a00de6 · 0a00de6
1 parent 8f4dbf2
commit 0a00de6
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Showing 3 changed files with 38 additions and 40 deletions.
diff --git a/sam/models/base_model.py b/sam/models/base_model.py
@@ -697,17 +697,17 @@ def dump(
             backup, self.model_ = self.model_, None
 
         foldername = Path(foldername)
-        match model_file_extension:
-            case ".json":
-                import json
+        if model_file_extension == ".json":
+            import json
 
-                with open(foldername / (prefix + ".json"), "w") as file:
-                    json.dump(self.to_dict(), file)
-            case ".pkl":
-                import cloudpickle
+            with open(foldername / (prefix + ".json"), "w") as file:
+                json.dump(self.to_dict(), file)
+
+        if model_file_extension == ".pkl":
+            import cloudpickle
 
-                with open(foldername / (prefix + ".pkl"), "wb") as file:
-                    cloudpickle.dump(self, file)
+            with open(foldername / (prefix + ".pkl"), "wb") as file:
+                cloudpickle.dump(self, file)
 
         if backup is not None:
             self.model_ = backup

diff --git a/sam/models/constant_model.py b/sam/models/constant_model.py
@@ -294,22 +294,21 @@ def predict(
     def dump_parameters(
         self, foldername: str, prefix: str = "model", file_extension=".json"
     ) -> None:
-        match file_extension:
-            case ".json":
-                parameters = vars(self.model_)
-                parameters["model_quantiles_"] = parameters["model_quantiles_"].tolist()
-                with open(Path(foldername) / f"{prefix}_params.json", "w") as f:
-                    json.dump(obj=parameters, fp=f)
-            case ".pkl":
-                import cloudpickle
-
-                with open(Path(foldername) / f"{prefix}_params.pkl", "wb") as f:
-                    cloudpickle.dump(self.model_, f)
-            case _:
-                raise ValueError(
-                    f"The file extension: {file_extension} "
-                    f"is not supported choose '.pkl' or '.json'"
-                )
+        if file_extension == ".json":
+            parameters = vars(self.model_)
+            parameters["model_quantiles_"] = parameters["model_quantiles_"].tolist()
+            with open(Path(foldername) / f"{prefix}_params.json", "w") as f:
+                json.dump(obj=parameters, fp=f)
+            return
+        if file_extension == ".pkl":
+            import cloudpickle
+
+            with open(Path(foldername) / f"{prefix}_params.pkl", "wb") as f:
+                cloudpickle.dump(self.model_, f)
+            return
+        raise ValueError(
+            f"The file extension: {file_extension} " f"is not supported choose '.pkl' or '.json'"
+        )
 
     @staticmethod
     def load_parameters(obj, foldername: str, prefix: str = "model") -> Any:

diff --git a/sam/models/mlp_model.py b/sam/models/mlp_model.py
@@ -384,21 +384,20 @@ def dump_parameters(
 
         check_is_fitted(self, "model_")
         foldername = Path(foldername)
-        match file_extension:
-            case ".onnx":
-                input_signature = [tf.TensorSpec((None, *self.input_shape), name="X")]
-                onnx_model, _ = tf2onnx.convert.from_keras(
-                    self.model_, input_signature=input_signature, opset=13
-                )
-                onnx.save(onnx_model, foldername / (prefix + ".onnx"))
-            case ".h5":
-                self.model_.save(foldername / (prefix + ".h5"))
-
-            case _:
-                raise ValueError(
-                    f"The file extension: {file_extension} "
-                    f"is not supported choose '.pkl' or '.json'"
-                )
+        if file_extension == ".onnx":
+            input_signature = [tf.TensorSpec((None, *self.input_shape), name="X")]
+            onnx_model, _ = tf2onnx.convert.from_keras(
+                self.model_, input_signature=input_signature, opset=13
+            )
+            onnx.save(onnx_model, foldername / (prefix + ".onnx"))
+            return
+        if file_extension == ".h5":
+            self.model_.save(foldername / (prefix + ".h5"))
+            return
+
+        raise ValueError(
+            f"The file extension: {file_extension} " f"is not supported choose '.pkl' or '.json'"
+        )
 
     @staticmethod
     def load_parameters(obj, foldername: str, prefix: str = "model") -> Any: