================
@@ -735,31 +735,22 @@ void CIRGenFunction::emitCXXAggrConstructorCall(
// are probably legitimate places where we could assume that this
// doesn't happen, but it's not clear that it's worth it.
- auto arrayTy = mlir::cast<cir::ArrayType>(arrayBase.getElementType());
- mlir::Type elementType = arrayTy.getElementType();
-
- // This might be a multi-dimensional array. Find the innermost element type.
+ // Peel any array types wrapped in the address element type down to the CIR
+ // type of a single constructed object.
+ mlir::Type elementType = arrayBase.getElementType();
while (auto maybeArrayTy = mlir::dyn_cast<cir::ArrayType>(elementType))
elementType = maybeArrayTy.getElementType();
cir::PointerType ptrToElmType = builder.getPointerTo(elementType);
- // Optimize for a constant count.
- if (auto constantCount = numElements.getDefiningOp<cir::ConstantOp>()) {
- if (auto constIntAttr = constantCount.getValueAttr<cir::IntAttr>()) {
- // Just skip out if the constant count is zero.
- if (constIntAttr.getUInt() == 0)
- return;
-
- arrayTy = cir::ArrayType::get(elementType, constIntAttr.getUInt());
- // Otherwise, emit the check.
- }
-
- if (constantCount.use_empty())
- constantCount.erase();
- } else {
- // Otherwise, emit the check.
- cgm.errorNYI(e->getSourceRange(),
- "emitCXXAggrConstructorCall: dynamic-length array
expression");
+ bool useDynamicArrayCtor = true;
+ uint64_t constElementCount = 0;
+ if (auto constantOp = numElements.getDefiningOp<cir::ConstantOp>()) {
+ constElementCount = CIRGenFunction::getZExtIntValueFromConstOp(constantOp);
+ if (constElementCount == 0)
----------------
andykaylor wrote:
I guess this gets into the philosophical debate about how much optimization the
front end should do. If the folding is really trivial, we'll have done it
before we get here. For instance, the code below gets us here with a constant 4:
```
struct S {
S();
};
void foo() {
S *p = new S[2+2];
}
```
The case you mentioned with a temporary that has a single assigned value would
require some more extensive analysis.
https://github.com/llvm/llvm-project/pull/190656
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