[Mlir-commits] [mlir] [MLIR][Shape] Support >2 args in `shape.broadcast` folder (PR #126808)

[Jacques Pienaar]

================
@@ -649,24 +649,32 @@ OpFoldResult BroadcastOp::fold(FoldAdaptor adaptor) {
     return getShapes().front();
   }
 
-  // TODO: Support folding with more than 2 input shapes
-  if (getShapes().size() > 2)
+  if (!adaptor.getShapes().front())
     return nullptr;
 
-  if (!adaptor.getShapes()[0] || !adaptor.getShapes()[1])
-    return nullptr;
-  auto lhsShape = llvm::to_vector<6>(
-      llvm::cast<DenseIntElementsAttr>(adaptor.getShapes()[0])
-          .getValues<int64_t>());
-  auto rhsShape = llvm::to_vector<6>(
-      llvm::cast<DenseIntElementsAttr>(adaptor.getShapes()[1])
+  auto firstShape = llvm::to_vector<6>(
+      llvm::cast<DenseIntElementsAttr>(adaptor.getShapes().front())
           .getValues<int64_t>());
+
   SmallVector<int64_t, 6> resultShape;
+  resultShape.clear();
+  std::copy(firstShape.begin(), firstShape.end(), std::back_inserter(resultShape));
 
-  // If the shapes are not compatible, we can't fold it.
-  // TODO: Fold to an "error".
-  if (!OpTrait::util::getBroadcastedShape(lhsShape, rhsShape, resultShape))
-    return nullptr;
+  for (auto next : adaptor.getShapes().drop_front()) {
+    if (!next)
+      return nullptr;
+    auto nextShape = llvm::to_vector<6>(
----------------
jpienaar wrote:

Yes, semi. If I recall it was either the default elsewhere in an ML framework where this was used or the max rank along set of ML models. But it is a bit arbitrary. Elsewhere folks also use the default of SmallVector. (The latter is probably a little bit more arbitrary, but neither is very fine tuned).

https://github.com/llvm/llvm-project/pull/126808