mlir::dyn_cast_or_null<mlir::StringAttr>(dict_attr.get("outputs"))) {
    str.getValue().split(output_names, ',', /*MaxSplit=*/-1,
                         /*KeepEmpty=*/false);
    auto term = fn.back().getTerminator();
    if (output_names.size() != term->getNumOperands()) {
      fn.emitWarning() << "output names (" << output_names.size()
                       << ") != terminator operands (" << term->getNumOperands()

    }
    // Returns -1 if we don't find which this result maps to.
    return -1;
  };

  llvm::SmallVector<Value, 4> returns;
  for (auto res : func.getBody().back().getTerminator()->getOperands()) {
    returns.push_back(res);
  }
  llvm::DenseMap<int, int> result;
  for (const auto &result_and_idx : llvm::enumerate(returns)) {
    if (IsTensorListType(result_and_idx.value().getType(),

    // argument can be easily found.
    bool unchanged = true;
    auto& body_block = while_op.getBody().front();
    auto& cond_block = while_op.getCond().front();
    auto& yield = *body_block.getTerminator();
    for (auto ba : body_block.getArguments()) {
      int arg_no = ba.getArgNumber();
      // Skip removing resources that are not read-only variables.

void ReplaceReturnOp(Region& region, PatternRewriter& rewriter) {
  OpBuilder::InsertionGuard guard(rewriter);

  for (auto& block : region.getBlocks()) {
    Operation* terminator = block.getTerminator();
    auto return_op = llvm::dyn_cast_or_null<mhlo::ReturnOp>(terminator);
    if (return_op == nullptr) continue;

    rewriter.setInsertionPoint(return_op);
    rewriter.replaceOpWithNewOp<TF::YieldOp>(return_op,