Rename ONNX un-/structuring hooks and adjust docstrings

baybe/surrogates/base.py

@@ -154,8 +154,10 @@ def _fit(self, searchspace: SearchSpace, train_x: Tensor, train_y: Tensor) -> No
         """
 
 
-def _decode_onnx_str(raw_unstructure_hook: UnstructureHook) -> UnstructureHook:
-    """Decode ONNX string for serialization purposes."""
+def _make_hook_decode_onnx_str(
+    raw_unstructure_hook: UnstructureHook
+) -> UnstructureHook:
+    """Wrap an unstructuring hook to let it also decode the contained ONNX string."""
 
     def wrapper(obj: StructuredValue) -> UnstructuredValue:
         dct = raw_unstructure_hook(obj)
@@ -167,8 +169,8 @@ def wrapper(obj: StructuredValue) -> UnstructuredValue:
     return wrapper
 
 
-def _encode_onnx_str(raw_structure_hook: StructureHook) -> StructureHook:
-    """Encode ONNX string for deserialization purposes."""
+def _make_hook_encode_onnx_str(raw_structure_hook: StructureHook) -> StructureHook:
+    """Wrap a structuring hook to let it also encode the contained ONNX string."""
 
     def wrapper(dct: UnstructuredValue, _: TargetType) -> StructuredValue:
         if (onnx_str := dct.get("onnx_str")) and isinstance(onnx_str, str):
@@ -211,12 +213,12 @@ def wrapper(obj: StructuredValue) -> UnstructuredValue:
 #   existing hooks of the concrete subclasses.
 converter.register_unstructure_hook(
     Surrogate,
-    _decode_onnx_str(
+    _make_hook_decode_onnx_str(
         _block_serialize_custom_architecture(
             lambda x: unstructure_base(x, overrides={"_model": override(omit=True)})
         )
     ),
 )
 converter.register_structure_hook(
-    Surrogate, _encode_onnx_str(get_base_structure_hook(Surrogate))
+    Surrogate, _make_hook_encode_onnx_str(get_base_structure_hook(Surrogate))
 )