[Mlir-commits] [mlir] [mlir][Math] Fix 0-rank support for PolynomialApproximation (PR #114826)

[Benjamin Maxwell]

================
@@ -43,20 +43,18 @@ using namespace mlir::vector;
 struct VectorShape {
   ArrayRef<int64_t> sizes;
   ArrayRef<bool> scalableFlags;
-
-  bool empty() const { return sizes.empty(); }
 };
 
 // Returns vector shape if the type is a vector. Returns an empty shape if it is
 // not a vector.
-static VectorShape vectorShape(Type type) {
+static std::optional<VectorShape> vectorShape(Type type) {
   auto vectorType = dyn_cast<VectorType>(type);
-  return vectorType
-             ? VectorShape{vectorType.getShape(), vectorType.getScalableDims()}
-             : VectorShape{};
+  return vectorType ? std::optional(VectorShape{vectorType.getShape(),
+                                                vectorType.getScalableDims()})
+                    : std::nullopt;
----------------
MacDue wrote:

nit: I think this is simpler without the ternary now. 
```suggestion
  if (vectorType)
    return VectorShape{vectorType.getShape(), vectorType.getScalableDims()};
  return std::nullopt;
```

https://github.com/llvm/llvm-project/pull/114826