: error_node_(error_node), error_device_(error_device) {}
  absl::Status Run(const std::string& function_name,
                   const tensorflow::DeviceSet& device_set,
                   const tensorflow::ConfigProto& config_proto,
                   const FunctionOptions& function_options,
                   std::unique_ptr<tensorflow::Graph>* graph,
                   tensorflow::FunctionLibraryDefinition* flib_def,

static TF_Operation* ToTF_Operation(Node* node) {
  return static_cast<TF_Operation*>(static_cast<void*>(node));
}

void TF_EnableXLACompilation(TF_SessionOptions* options, unsigned char enable) {
  tensorflow::ConfigProto& config = options->options.config;
  auto* optimizer_options =
      config.mutable_graph_options()->mutable_optimizer_options();
  if (enable) {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::ON_1);

                  size_t proto_len, TF_Status* status) {
  if (!options->options.config.ParseFromArray(proto, proto_len)) {
    status->status = InvalidArgument("Unparseable ConfigProto");
  }
  // Disable optimizations for static graph to allow calls to Session::Extend.
  options->options.config.mutable_experimental()
      ->set_disable_optimize_for_static_graph(true);
}

* Add an option `disable_eager_executer_streaming_enqueue` to `tensorflow.ConfigProto.Experimental` to control the eager runtime's behavior around parallel remote function invocations; when set to `True`, the eager runtime will be allowed to execute multiple function invocations in parallel.