} else if (auto island =
                   llvm::dyn_cast<mlir::tf_executor::IslandOp>(inst)) {
      Operation& inner_op = island.GetBody().front();
      auto op_name = GetTensorFlowOpName(inner_op.getName().getStringRef());
      if (llvm::isa<FuncOp>(inner_op) && op_name.ok()) {
        // If it is TF Control dialect specific op, look up custom operation

    } else if (auto island =
                   llvm::dyn_cast<mlir::tf_executor::IslandOp>(inst)) {
      Operation& inner_op = island.GetBody().front();
      auto op_name = GetTensorFlowOpName(inner_op.getName().getStringRef());
      if (llvm::isa<FuncOp>(inner_op) && op_name.ok()) {
        // If it is TF Control dialect specific op, look up custom operation

        }
        auto attr_value =
            mlir::DenseI32ArrayAttr::get(inner_op->getContext(), values);
        inner_op->setAttr(attr_name, attr_value);
      };

  if (inner_op->hasTrait<mlir::OpTrait::AttrSizedOperandSegments>() ||
      inner_op->hasTrait<mlir::OpTrait::AttrSizedResultSegments>()) {
    // The op has multiple variadic operands or results.

		//		if ind < end
		//		then goto enter_loop
		//		else goto exit_loop
		//
		//	enter_loop:
		//		do something without using ind nor nxt
		//		nxt = inc + ind
		//		goto loop
		//
		//	exit_loop:
		//
		// is rewritten to:
		//
		//	loop:
		//		ind = (Phi end nxt)
		//		if (Const [x]) < ind
		//		then goto enter_loop
		//		else goto exit_loop
		//
		//	enter_loop:

      control_nodes_at.try_emplace(&item.value(), item.index());
    }
  }

  for (auto outer_op : control_nodes) {
    auto control_node_op = dyn_cast<mlir::TFL::ControlNodeOp>(outer_op);
    auto* inner_op = &control_node_op.getBody().front().front();
    auto control_token = control_node_op.getControl();

    // Now go through all uses. Since *block is in executable order, control