if (auto device_attr =
          func.getArgAttrOfType<mlir::StringAttr>(index, kDeviceAttr))
    *node_def->mutable_device() = device_attr.getValue().str();

  llvm::ArrayRef<mlir::NamedAttribute> func_arg_i_attrs =
      mlir::function_interface_impl::getArgAttrs(func, index);
  absl::flat_hash_set<absl::string_view> attrs_to_ignore = {kDeviceAttr,

  if (auto device_attr =
          func.getArgAttrOfType<mlir::StringAttr>(index, kDeviceAttr))
    *node_def->mutable_device() = device_attr.getValue().str();

  llvm::ArrayRef<mlir::NamedAttribute> func_arg_i_attrs =
      mlir::function_interface_impl::getArgAttrs(func, index);
  absl::flat_hash_set<absl::string_view> attrs_to_ignore = {kDeviceAttr,

              << " but enclosing XlaCallModule has a function list of size "
              << function_list.size();
          return WalkResult::interrupt();
        }

        llvm::SmallVector<NamedAttribute> new_config;
        // Copy the attributes in the current config except `called_index`.
        for (auto attr : backend_config) {
          if (attr.getName() != kCalledIndexAttrName) {

// Signature:
// void mlir::BuiltinOptions{id}ToAttributes(
//     tflite::BuiltinOptions{id}Union op_union,
//     mlir::Builder builder,
//     llvm::SmallVectorImpl<mlir::NamedAttribute> &attributes);
//
// where id is an empty string if builtin_options_id is 1, or builtin_options_id
// otherwise.
static void EmitBuiltinOptionsToAttributes(const RecordKeeper &record_keeper,

    const llvm::DenseMap<Value, llvm::StringRef>& value_to_device) {
  // We apply all result attributes at once to avoid excessive allocations when
  // we have many result values.
  llvm::SmallVector<std::vector<NamedAttribute>, 8> result_attrs;
  {
    llvm::SmallVector<DictionaryAttr, 8> tmp;
    func.getAllResultAttrs(tmp);

    for (const auto& res : tmp) {
      result_attrs.push_back(res.getValue().vec());
    }
  }

                            rewriter.getIntegerType(64)),
      padding_nums);
  return padding_attr;
}

template <typename UniformQuantizedConvolutionOp>
FailureOr<SmallVector<NamedAttribute>> ConvertToMhloConvolutionOpAttrs(
    UniformQuantizedConvolutionOp op, PatternRewriter &rewriter) {
  // TODO(b/261005147): Update the lowering logic after migration to mhlo
  // ConvolutionDimensionNumbers.

      llvm::ArrayRef<Type>{RankedTensorType::get({ShapedType::kDynamic},
                                                 builder->getIntegerType(64))},
      llvm::ArrayRef<Value>{compilation_key},
      llvm::ArrayRef<NamedAttribute>{
          builder->getNamedAttr("index",
                                builder->getI64IntegerAttr(execute_arg_index)),
          builder->getNamedAttr("is_output", builder->getBoolAttr(false))});
}

    auto bad_consumers =
        b.getNamedAttr("bad_consumers", b.getI32ArrayAttr({1, 2, 3, 4}));

    module->setAttr("tf.versions",
                    b.getDictionaryAttr(llvm::ArrayRef<mlir::NamedAttribute>(
                        {producer, min_consumer, bad_consumers})));

    return run_status_;
  }

  Status run_status_;
};

FunctionDef XTimesTwo() {

    for (auto [value, aggregator_id] :
         llvm::zip_equal(quantizable_values, aggregator_ids)) {
      // ID attribute will have empty value for now.
      SmallVector<NamedAttribute, 5> attributes{
          rewriter.getNamedAttr("id", rewriter.getStringAttr(aggregator_id)),
          rewriter.getNamedAttr(
              "calibration_method",

  auto rendezvous_name = StringAttr::get(context, formatted_key);
  auto rendezvous_name_attr = NamedAttribute(
      StringAttr::get(context, xla::kXlaHostTransferRendezvousNameAttr),
      rendezvous_name);

  auto host_handler_name_value =
      StringAttr::get(context, host_handler_name.str());
  auto host_handler_name_attr = NamedAttribute(
      StringAttr::get(context, xla::kXlaHostTransferHandlerNameAttr),