Automerge: [mlir][Vector] Fix vector.shuffle folder for poison indices (#124863)

This PR fixes the folder of a `vector.shuffle` with constant input
vectors in the presence of a poison index. Partially poison vectors are
currently not supported in UB so the folder select v1[0] for elements
indexed by poison.

Author: dcaballe

mlir/lib/Dialect/Vector/IR/VectorOps.cpp

@@ -2673,43 +2673,51 @@ static bool isStepIndexArray(ArrayRef<T> idxArr, uint64_t begin, size_t width) {
 }
 
 OpFoldResult vector::ShuffleOp::fold(FoldAdaptor adaptor) {
-  VectorType v1Type = getV1VectorType();
+  auto v1Type = getV1VectorType();
+  auto v2Type = getV2VectorType();
+
+  assert(!v1Type.isScalable() && !v2Type.isScalable() &&
+         "Vector shuffle does not support scalable vectors");
+
   // For consistency: 0-D shuffle return type is 1-D, this cannot be a folding
   // but must be a canonicalization into a vector.broadcast.
   if (v1Type.getRank() == 0)
     return {};
 
-  // fold shuffle V1, V2, [0, 1, 2, 3] : <4xi32>, <2xi32> -> V1
-  if (!v1Type.isScalable() &&
-      isStepIndexArray(getMask(), 0, v1Type.getDimSize(0)))
+  // Fold shuffle V1, V2, [0, 1, 2, 3] : <4xi32>, <2xi32> -> V1.
+  auto mask = getMask();
+  if (isStepIndexArray(mask, 0, v1Type.getDimSize(0)))
     return getV1();
-  // fold shuffle V1, V2, [4, 5] : <4xi32>, <2xi32> -> V2
-  if (!getV1VectorType().isScalable() && !getV2VectorType().isScalable() &&
-      isStepIndexArray(getMask(), getV1VectorType().getDimSize(0),
-                       getV2VectorType().getDimSize(0)))
+  // Fold shuffle V1, V2, [4, 5] : <4xi32>, <2xi32> -> V2.
+  if (isStepIndexArray(mask, v1Type.getDimSize(0), v2Type.getDimSize(0)))
     return getV2();
 
-  Attribute lhs = adaptor.getV1(), rhs = adaptor.getV2();
-  if (!lhs || !rhs)
+  Attribute v1Attr = adaptor.getV1(), v2Attr = adaptor.getV2();
+  if (!v1Attr || !v2Attr)
     return {};
 
-  auto lhsType =
-      llvm::cast<VectorType>(llvm::cast<DenseElementsAttr>(lhs).getType());
   // Only support 1-D for now to avoid complicated n-D DenseElementsAttr
   // manipulation.
-  if (lhsType.getRank() != 1)
+  if (v1Type.getRank() != 1)
     return {};
-  int64_t lhsSize = lhsType.getDimSize(0);
+
+  int64_t v1Size = v1Type.getDimSize(0);
 
   SmallVector<Attribute> results;
-  auto lhsElements = llvm::cast<DenseElementsAttr>(lhs).getValues<Attribute>();
-  auto rhsElements = llvm::cast<DenseElementsAttr>(rhs).getValues<Attribute>();
-  for (int64_t i : this->getMask()) {
-    if (i >= lhsSize) {
-      results.push_back(rhsElements[i - lhsSize]);
+  auto v1Elements = cast<DenseElementsAttr>(v1Attr).getValues<Attribute>();
+  auto v2Elements = cast<DenseElementsAttr>(v2Attr).getValues<Attribute>();
+  for (int64_t maskIdx : mask) {
+    Attribute indexedElm;
+    // Select v1[0] for poison indices.
+    // TODO: Return a partial poison vector when supported by the UB dialect.
+    if (maskIdx == ShuffleOp::kPoisonIndex) {
+      indexedElm = v1Elements[0];
     } else {
-      results.push_back(lhsElements[i]);
+      indexedElm =
+          maskIdx < v1Size ? v1Elements[maskIdx] : v2Elements[maskIdx - v1Size];
     }
+
+    results.push_back(indexedElm);
   }
 
   return DenseElementsAttr::get(getResultVectorType(), results);

mlir/test/Dialect/Vector/canonicalize.mlir

@@ -2006,41 +2006,68 @@ func.func @shuffle_1d() -> vector<4xi32> {
   return %shuffle : vector<4xi32>
 }
 
+// -----
+
+// Check that poison indices pick the first element of the first non-poison
+// input vector. That is, %v[0] (i.e., 5) in this test.
+
+// CHECK-LABEL: func @shuffle_1d_poison_idx
+//       CHECK:   %[[V:.+]] = arith.constant dense<[2, 5, 0, 5]> : vector<4xi32>
+//       CHECK:   return %[[V]]
+func.func @shuffle_1d_poison_idx() -> vector<4xi32> {
+  %v0 = arith.constant dense<[5, 4, 3]> : vector<3xi32>
+  %v1 = arith.constant dense<[2, 1, 0]> : vector<3xi32>
+  %shuffle = vector.shuffle %v0, %v1 [3, -1, 5, -1] : vector<3xi32>, vector<3xi32>
+  return %shuffle : vector<4xi32>
+}
+
+// -----
+
 // CHECK-LABEL: func @shuffle_canonicalize_0d
 func.func @shuffle_canonicalize_0d(%v0 : vector<i32>, %v1 : vector<i32>) -> vector<1xi32> {
   // CHECK: vector.broadcast %{{.*}} : vector<i32> to vector<1xi32>
   %shuffle = vector.shuffle %v0, %v1 [0] : vector<i32>, vector<i32>
   return %shuffle : vector<1xi32>
 }
 
+// -----
+
 // CHECK-LABEL: func @shuffle_fold1
 //       CHECK:   %arg0 : vector<4xi32>
 func.func @shuffle_fold1(%v0 : vector<4xi32>, %v1 : vector<2xi32>) -> vector<4xi32> {
   %shuffle = vector.shuffle %v0, %v1 [0, 1, 2, 3] : vector<4xi32>, vector<2xi32>
   return %shuffle : vector<4xi32>
 }
 
+// -----
+
 // CHECK-LABEL: func @shuffle_fold2
 //       CHECK:   %arg1 : vector<2xi32>
 func.func @shuffle_fold2(%v0 : vector<4xi32>, %v1 : vector<2xi32>) -> vector<2xi32> {
   %shuffle = vector.shuffle %v0, %v1 [4, 5] : vector<4xi32>, vector<2xi32>
   return %shuffle : vector<2xi32>
 }
 
+// -----
+
 // CHECK-LABEL: func @shuffle_fold3
 //       CHECK:   return %arg0 : vector<4x5x6xi32>
 func.func @shuffle_fold3(%v0 : vector<4x5x6xi32>, %v1 : vector<2x5x6xi32>) -> vector<4x5x6xi32> {
   %shuffle = vector.shuffle %v0, %v1 [0, 1, 2, 3] : vector<4x5x6xi32>, vector<2x5x6xi32>
   return %shuffle : vector<4x5x6xi32>
 }
 
+// -----
+
 // CHECK-LABEL: func @shuffle_fold4
 //       CHECK:   return %arg1 : vector<2x5x6xi32>
 func.func @shuffle_fold4(%v0 : vector<4x5x6xi32>, %v1 : vector<2x5x6xi32>) -> vector<2x5x6xi32> {
   %shuffle = vector.shuffle %v0, %v1 [4, 5] : vector<4x5x6xi32>, vector<2x5x6xi32>
   return %shuffle : vector<2x5x6xi32>
 }
 
+// -----
+
 // CHECK-LABEL: func @shuffle_nofold1
 //       CHECK:   %[[V:.+]] = vector.shuffle %arg0, %arg1 [0, 1, 2, 3, 4] : vector<4xi32>, vector<2xi32>
 //       CHECK:   return %[[V]]