Fix or comment other minor comments in PR #12

Deeploy/Targets/Generic/TypeCheckers.py

@@ -125,19 +125,11 @@ def _inferSignedness(self, inputs: List[VariableBuffer],
             return [False]
 
 
-class FloatAddChecker(SignPropTypeChecker):
+class FloatAddChecker(NodeTypeChecker):
 
     def __init__(self, input_types: Sequence[Type[Pointer]], output_types: Sequence[Type[Pointer]]):
         super().__init__(input_types, output_types)
 
-    def _inferNumLevels(self, inputs: List[VariableBuffer],
-                        operatorRepresentation: OperatorRepresentation) -> List[int]:
-        return [inputs[0].nLevels + inputs[1].nLevels]
-
-    def _inferSignedness(self, inputs: List[VariableBuffer],
-                         operatorRepresentation: OperatorRepresentation) -> List[bool]:
-        return [True]
-
 
 class GatherChecker(SignPropTypeChecker):
 

DeeployTest/testUtils/typeMapping.py

@@ -75,6 +75,9 @@ def inferInputType(_input: np.ndarray,
 
     matchingTypes = []
 
+    # FIXME: this is okay for now (3 distinctions are fine), but there is implicit
+    # knowledge encoded in the order of the checks (i.e. first unsigned, signed
+    # and then float). It might be good to extract that implicit knowledge into an ordered list.
     if signProp and isUnsigned(_input) and isInteger(_input):
         for _type in sorted(signedPlatformTypes, key = lambda x: x.typeWidth):
             signPropOffset = (2**(_type.typeWidth - 1))