[mlir][linalg] Add helpers for linalg.tiled_loop [nfc].

mlir/include/mlir/Dialect/Linalg/IR/LinalgOps.td

let builders = [
     OpBuilder<(ins "ValueRange":$lowerBounds, "ValueRange":$upperBounds,
       "ValueRange":$steps, "ValueRange":$inputs, "ValueRange":$outputs,
       "ArrayAttr":$iteratorTypes,
       CArg<"function_ref<void (OpBuilder &, Location, ValueRange)>",
            "nullptr">:$bodyBuilderFn)>,
   ];
 
   let extraClassDeclaration = [{
+    /// Number of operands controlling the loop: lbs, ubs, steps
+    unsigned getNumControlOperands() { return 3 * getNumLoops(); }
+
     ValueRange getInductionVars() {
       return getBody()->getArguments();
     }
+
+   /// Result that corresponds to the `outputs` argument of tensor type.
+   OpResult getTiedOpResult(OpOperand& opOperand) {
+      // No result can correspond to a memref argument.
+      if (opOperand.get().getType().isa<MemRefType>()) return OpResult();
+
+      // Check whether the operand index is in bounds of `outputs()` arg.
+      int operandIndex = opOperand.getOperandNumber();
+      int outputIndexStart =
+          getNumControlOperands() + inputs().size();
+      int outputIndexEnd = outputIndexStart + outputs().size();
+      if (operandIndex < outputIndexStart || operandIndex >= outputIndexEnd)
+        return OpResult();
+
+      // Count tensor arguments in `outputs` to compute the result index.
+      int tensorId = -1;
+      for (int i = outputIndexStart; i <= operandIndex; ++i)
+        tensorId += getOperand(i).getType().isa<RankedTensorType>();
+      return getOperation()->getResult(tensorId);
+    }
+
     unsigned getNumLoops() { return step().size(); }
   }];
 
   let hasCanonicalizer = 1;
   let hasFolder = 1;
 }
 
 
 #endif // LINALG_OPS