[mlir][linalg] Cleanup LinalgOp usage in bufferize, detensorize, and interchange.

[gysit]

Summary

Replace the uses of deprecated Structured Op Interface methods in Bufferize.cpp, Detensorize.cpp, and Interchange.cpp. The patch is based on https://reviews.llvm.org/D103394.

mlir/lib/Dialect/Linalg/Transforms/Bufferize.cpp

if (tensorType == nullptr) {
           << "tensor to buffer conversion expects ranked tensor results";
       return failure();
     }
     auto tensorShape = tensorType.getShape();
     auto memrefType = MemRefType::get(tensorShape, tensorType.getElementType());
     Value resultTensor = outputs[resultIndex];
 
     // Clone output buffers whose value is actually used.
-    if (linalgOp.payloadUsesValueFromOutputOperandIndex(resultIndex)) {
+    OpOperand *tiedOpOperand = linalgOp.getOutputOperand(resultIndex);
+    if (linalgOp.payloadUsesValueFromOperand(tiedOpOperand)) {
       resultBuffers.push_back(cloneMemref(loc, resultTensor, b));
       continue;
     }
 
     // Allocate buffers for statically-shaped results.
     if (memrefType.hasStaticShape()) {
       resultBuffers.push_back(b.create<memref::AllocOp>(loc, memrefType));
       continue;

mlir/lib/Dialect/Linalg/Transforms/Detensorize.cpp

 ///
 /// Returns true if tensorType can be detensored.
 bool canBeDetensored(TensorType tensorType) {
   return tensorType.hasRank() && tensorType.getRank() == 0;
 }
 
 bool shouldBeDetensored(Operation *op, TypeConverter typeConverter) {
   GenericOp genericOp = dyn_cast_or_null<GenericOp>(op);
-  return genericOp && llvm::all_of(genericOp.getShapedOperandTypes(),
-                                   [&](ShapedType shapedType) {
-                                     return !typeConverter.isLegal(shapedType);
-                                   });
+  return genericOp &&
+         llvm::all_of(
+             genericOp.getInputAndOutputOperands(), [&](OpOperand *opOperand) {
+               return !typeConverter.isLegal(opOperand->get().getType());
 }
 
 /// A conversion patttern for detensoring `linalg.generic` ops.
 class DetensorizeGenericOp : public OpConversionPattern<GenericOp> {
 public:
   using OpConversionPattern::OpConversionPattern;
   LogicalResult
   matchAndRewrite(GenericOp op, ArrayRef<Value> operands,

mlir/lib/Dialect/Linalg/Transforms/Interchange.cpp

void mlir::linalg::interchangeGenericOp(PatternRewriter &rewriter,
   AffineMap permutationMap = inversePermutation(
       AffineMap::getPermutationMap(interchangeVector, context));
   assert(permutationMap && "expected permutation to be invertible");
   assert(interchangeVector.size() == genericOp.getNumLoops() &&
          "expected interchange vector to have entry for every loop");
 
   // 2. Compute the interchanged indexing maps.
   SmallVector<Attribute, 4> newIndexingMaps;
-  ArrayRef<Attribute> indexingMaps = genericOp.indexing_maps().getValue();
-  for (unsigned i = 0, e = genericOp.getNumShapedOperands(); i != e; ++i) {
-    AffineMap m = indexingMaps[i].cast<AffineMapAttr>().getValue();
+  for (OpOperand *opOperand : genericOp.getInputAndOutputOperands()) {
+    AffineMap m = genericOp.getTiedIndexingMap(opOperand);
     if (!permutationMap.isEmpty())
       m = m.compose(permutationMap);
     newIndexingMaps.push_back(AffineMapAttr::get(m));
   }
   genericOp->setAttr(getIndexingMapsAttrName(),
                      ArrayAttr::get(context, newIndexingMaps));
 
   // 3. Compute the interchanged iterator types.