[mlir][nfc] Clarify the limitation on scalable vectors

When converting/lowering to LLVM, MLIR does not support n-D scalable
vectors at the moment. This patch simply clarifies an assert that's
meant to catch such unsupported cases.

Note that we may want to relax this condition in the future.

Differential Revision: https://reviews.llvm.org/D154302

diff --git a/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp b/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp
index 4ca5c75..9e03e2f 100644 (file)
--- a/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp
+++ b/mlir/lib/Conversion/LLVMCommon/TypeConverter.cpp
@@ -457,6 +457,9 @@ Type LLVMTypeConverter::convertMemRefToBarePtr(BaseMemRefType type) {
 ///  * 1-D `vector<axT>` remains as is while,
 ///  * n>1 `vector<ax...xkxT>` convert via an (n-1)-D array type to
 ///    `!llvm.array<ax...array<jxvector<kxT>>>`.
+/// As LLVM does not support arrays of scalable vectors, it is assumed that
+/// scalable vectors are always 1-D. This condition could be relaxed once the
+/// missing functionality is added in LLVM
 Type LLVMTypeConverter::convertVectorType(VectorType type) {
   auto elementType = convertType(type.getElementType());
   if (!elementType)
@@ -467,8 +470,9 @@ Type LLVMTypeConverter::convertVectorType(VectorType type) {
                                     type.getScalableDims().back());
   assert(LLVM::isCompatibleVectorType(vectorType) &&
          "expected vector type compatible with the LLVM dialect");
-  assert((type.isScalable() == type.allDimsScalable()) &&
-         "expected scalable vector with all dims scalable");
+  assert(
+      (!type.isScalable() || (type.getRank() == 1)) &&
+      "expected 1-D scalable vector (n-D scalable vectors are not supported)");
   auto shape = type.getShape();
   for (int i = shape.size() - 2; i >= 0; --i)
     vectorType = LLVM::LLVMArrayType::get(vectorType, shape[i]);