diff --git a/test/from_linalg_invalid.mlir b/test/from_linalg_invalid.mlir
index 0c18b29b..bfb010b2 100644
--- a/test/from_linalg_invalid.mlir
+++ b/test/from_linalg_invalid.mlir
@@ -11,7 +11,7 @@
 }
 
 func @reductions(%arg0: memref<2x3x4x5x6xf32>, %arg1: memref<2x4x6xf32>) {
-  // expected-error @+1 {{Linalg op is not compatible with Sair}}
+  // expected-error @+1 {{unexpected output tensor expression in indexing map #0 a.k.a 'd3' is function of reduction iterator 'd3'}}
   linalg.generic #reductions_trait
     ins(%arg0 : memref<2x3x4x5x6xf32>)
    outs(%arg1 : memref<2x4x6xf32>) {
diff --git a/transforms/sair_from_linalg.cc b/transforms/sair_from_linalg.cc
index be99e55c..a14eafad 100644
--- a/transforms/sair_from_linalg.cc
+++ b/transforms/sair_from_linalg.cc
@@ -431,7 +431,7 @@ void MoveBodyBlock(mlir::AffineMap linalg_to_sair_loops,
 // as "types" and a hyper-rectangular domain with the given number of dimensons.
 // Uses "rewriter" to construct the types.
 void CreateResultTypes(mlir::Builder &rewriter, int num_dimensions,
-                       mlir::TypeRange types,
+                       const SmallVectorImpl<MemRefType> &types,
                        llvm::SmallVectorImpl<mlir::Type> &result_types) {
   mlir::MLIRContext *context = rewriter.getContext();
   auto result_domain_shape =
@@ -562,7 +562,7 @@ mlir::LogicalResult RewriteLinalgToSair(mlir::linalg::LinalgOp op,
   // Linalg does not seem to restrict the output indexing to parallel dimensions
   // only, but Sair does. Abort the conversion in case of incompatibility.
   int num_parallel_loops = op.getNumParallelLoops();
-  int num_operands = op.getNumInputsAndOutputBuffers();
+  int num_operands = op.getNumShapedOperands();
   for (int i = op.getNumInputs(); i < num_operands; ++i) {
     auto mapping = operand_mappings[i].cast<MappingAttr>();
     if (mlir::failed(VerifyReductionMapping(mapping, num_parallel_loops))) {
@@ -589,20 +589,20 @@ mlir::LogicalResult RewriteLinalgToSair(mlir::linalg::LinalgOp op,
   // Convert input and input/output MemRefs used by Linalg to Sair values.
   llvm::SmallVector<mlir::Value, 4> map_operands;
   llvm::SmallVector<llvm::SmallVector<mlir::Value, 4>, 4> result_ranges;
-  EmitMemRefToValue(op.getInputsAndOutputBuffers(), op.getNumOutputs(), loc,
+  EmitMemRefToValue(op.getShapedOperands(), op.getNumOutputs(), loc,
                     sair_program, rewriter, map_operands, result_ranges);
 
   // Prepare parameters of the Sair map operation.
   int num_loops = op.getNumLoops();
   llvm::SmallVector<LoopBound, 8> loop_bounds;
-  CollectLoopBounds(num_loops, subscripts_to_loops,
-                    op.getInputsAndOutputBuffers(), loop_bounds);
+  CollectLoopBounds(num_loops, subscripts_to_loops, op.getShapedOperands(),
+                    loop_bounds);
   llvm::SmallVector<mlir::Value, 4> domain_ranges =
       CreateSairDomain(loc, loop_bounds, sair_program, rewriter);
 
   llvm::SmallVector<mlir::Type, 4> result_types;
-  CreateResultTypes(rewriter, num_parallel_loops,
-                    op.getOutputBuffers().getTypes(), result_types);
+  CreateResultTypes(rewriter, num_parallel_loops, op.getOutputBufferTypes(),
+                    result_types);
 
   // Construct the main map or map_reduce operation.
   mlir::Operation *map_op;