[mlir] Lower Shape binary ops (AddOp, MulOp) to Standard.

[frgossen]

mlir/lib/Conversion/ShapeToStandard/ShapeToStandard.cpp

23

nit: If these were called SrcOp/DstOp it could be clearer that these are operations, not types.

[pifon2a]

Addressed the comment.

[herhut]

Nice! Thanks.

[jpienaar]

mlir/lib/Conversion/ShapeToStandard/ShapeToStandard.cpp

31

What does the adaptor give you which the generated op doesn't?

mlir/lib/Conversion/ShapeToStandard/ShapeToStandard.cpp

 
 #include "../PassDetail.h"
 #include "mlir/Dialect/SCF/SCF.h"
 #include "mlir/Dialect/Shape/IR/Shape.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"
 #include "mlir/Transforms/DialectConversion.h"
 
 using namespace mlir;
+using namespace mlir::shape;
 
 namespace {
 
 /// Conversion patterns.
+template <typename SrcOpTy, typename DstOpTy>
+class BinaryOpConversion : public OpConversionPattern<SrcOpTy> {
+public:
+  using OpConversionPattern<SrcOpTy>::OpConversionPattern;
+
+  LogicalResult
+  matchAndRewrite(SrcOpTy op, ArrayRef<Value> operands,
+                  ConversionPatternRewriter &rewriter) const override {
+    typename SrcOpTy::OperandAdaptor adaptor(operands);
+    rewriter.replaceOpWithNewOp<DstOpTy>(op.getOperation(), adaptor.lhs(),
+                                         adaptor.rhs());
+    return success();
+  }
+};
+
 class FromExtentTensorOpConversion
     : public OpConversionPattern<shape::FromExtentTensorOp> {
 public:
   using OpConversionPattern<shape::FromExtentTensorOp>::OpConversionPattern;
 
   LogicalResult
   matchAndRewrite(shape::FromExtentTensorOp op, ArrayRef<Value> operands,
                   ConversionPatternRewriter &rewriter) const override {

 };
 
 } // namespace
 
 void mlir::populateShapeToStandardConversionPatterns(
     OwningRewritePatternList &patterns, MLIRContext *ctx) {
   // clang-format off
   patterns.insert<
+      BinaryOpConversion<AddOp, AddIOp>,
+      BinaryOpConversion<MulOp, MulIOp>,
       FromExtentTensorOpConversion,
       IndexToSizeOpConversion,
       SizeToIndexOpConversion,
       ToExtentTensorOpConversion>(ctx);
   // clang-format on
 }
 
 std::unique_ptr<OperationPass<ModuleOp>>
 mlir::createConvertShapeToStandardPass() {
   return std::make_unique<ConvertShapeToStandardPass>();
 }

mlir/test/Conversion/ShapeToStandard/shape-to-standard.mlir

 // CHECK-LABEL: @from_extent_tensor
 // CHECK-SAME: (%[[TENSOR:.*]]: tensor<?xindex>) -> tensor<?xindex>
 func @from_extent_tensor(%tensor : tensor<?xindex>) -> !shape.shape {
   // CHECK-NEXT: return %[[TENSOR]] : tensor<?xindex>
   %shape = "shape.from_extent_tensor"(%tensor)
       : (tensor<?xindex>) -> !shape.shape
   return %shape : !shape.shape
 }
+
+// -----
+
+// Lower binary ops.
+// CHECK-LABEL: @binary_ops
+// CHECK-SAME: (%[[LHS:.*]]: index, %[[RHS:.*]]: index)
+func @binary_ops(%lhs : !shape.size, %rhs : !shape.size) {
+  %sum = "shape.add"(%lhs, %rhs) : (!shape.size, !shape.size) -> !shape.size
+  // CHECK-NEXT: addi %[[LHS]], %[[RHS]] : index
+  %product = shape.mul %lhs, %rhs
+  // CHECK-NEXT: muli %[[LHS]], %[[RHS]] : index
+  return
+}