// https://llvm.discourse.group/t/should-we-have-0-d-vectors/3097.
// In the meantime, lower these to a scalar load when they pop up.
if (reducedShapeRank == 0) {
- Value newRead = rewriter.create<memref::LoadOp>(
- op.getLoc(), originalVecType.getElementType(), op.source(),
- op.indices());
+ Value newRead;
+ if (op.getShapedType().isa<TensorType>()) {
+ newRead = rewriter.create<tensor::ExtractOp>(op.getLoc(), op.source(),
+ op.indices());
+ } else {
+ newRead = rewriter.create<memref::LoadOp>(
+ op.getLoc(), originalVecType.getElementType(), op.source(),
+ op.indices());
+ }
rewriter.replaceOpWithNewOp<vector::BroadcastOp>(op, originalVecType,
newRead);
return success();
// RUN: mlir-opt %s -test-vector-transfer-lowering-patterns -canonicalize -split-input-file | FileCheck %s
-// CHECK-LABEL: func @vector_transfer_ops_0d(
+// CHECK-LABEL: func @vector_transfer_ops_0d_memref(
// CHECK-SAME: %[[MEM:.*]]: memref<f32>
// CHECK-SAME: %[[VV:.*]]: vector<1x1x1xf32>
-func @vector_transfer_ops_0d(%M: memref<f32>, %v: vector<1x1x1xf32>) {
+func @vector_transfer_ops_0d_memref(%M: memref<f32>, %v: vector<1x1x1xf32>) {
%f0 = arith.constant 0.0 : f32
// CHECK-NEXT: %[[V:.*]] = memref.load %[[MEM]][] : memref<f32>
// -----
+// CHECK-LABEL: func @vector_transfer_ops_0d_tensor(
+// CHECK-SAME: %[[SOURCE:.*]]: tensor<f32>
+func @vector_transfer_ops_0d_tensor(%M: tensor<f32>) -> vector<1xf32> {
+ %f0 = arith.constant 0.0 : f32
+
+// CHECK-NEXT: %[[S:.*]] = tensor.extract %[[SOURCE]][] : tensor<f32>
+// CHECK-NEXT: %[[V:.*]] = vector.broadcast %[[S]] : f32 to vector<1xf32>
+ %0 = vector.transfer_read %M[], %f0 {permutation_map = affine_map<()->(0)>} :
+ tensor<f32>, vector<1xf32>
+
+// CHECK-NEXT: return %[[V]]
+ return %0: vector<1xf32>
+}
+
+// -----
+
// transfer_read/write are lowered to vector.load/store
// CHECK-LABEL: func @transfer_to_load(
// CHECK-SAME: %[[MEM:.*]]: memref<8x8xf32>,