server_def.set_job_name("worker");
  server_def.set_task_index(0);
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->mutable_job(0);
  int worker_port = tensorflow::testing::PickUnusedPortOrDie();
  job_def->mutable_tasks()->at(0) =
      tensorflow::strings::StrCat("localhost:", worker_port);
  serialized = server_def.SerializeAsString();

  // eager runtime.
  if (enable_grappler) {
    tensorflow::ConfigProto config;
    // Do not skip grappler optimization even for small graphs.
    config.mutable_graph_options()
        ->mutable_rewrite_options()
        ->set_min_graph_nodes(-1);
    string serialized_config;
    ASSERT_TRUE(config.SerializeToString(&serialized_config));
    TFE_OpSetAttrString(

};

struct TF_DeprecatedSession {
  tensorflow::Session* session;
};

struct TF_Library {
  void* lib_handle;
  TF_Buffer op_list;
};

struct TF_Graph {
  TF_Graph();

  mutable tensorflow::mutex mu;
  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.

  Tensor input(tensorflow::DT_STRING, TensorShape({4}));
  for (int64_t i = 0; i < input.NumElements(); ++i) {
    tensorflow::Example example;
    auto* feature_map = example.mutable_features()->mutable_feature();
    (*feature_map)["x"].mutable_float_list()->add_value(i);
    input.flat<tstring>()(i) = example.SerializeAsString();
  }

  const tensorflow::string input_op_name(

  server_def.set_task_index(0);
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->add_job();
  job_def->set_name(job_name);
  for (int i = 0; i < num_tasks; i++) {
    int port = tensorflow::testing::PickUnusedPortOrDie();
    job_def->mutable_tasks()->insert(
        {i, tensorflow::strings::StrCat("localhost", ":", port)});

          NodeDef* const node_def = graph_def.add_node();
          *node_def = node->def();
        }
      }
      *graph_def.mutable_library() = graph.flib_def().ToProto();
      if (flags::Global().more_stack_traces.value()) {
        *graph_def.mutable_debug_info() = graph.BuildDebugInfo();
      }
      session->graph->mu.unlock();
      status->status = session->session->Extend(std::move(graph_def));

  // A cancellation manager to use if the caller does not provide one. When ops
  // are executed asynchronously this must outlive the queued op, so it can't be
  // function-local to Execute.
  mutable std::unique_ptr<CancellationManager> default_cancellation_manager_;
};

// Contains a tuple of tensors, one on each of the `underlying_devices_` of the
// ParallelDevice.
class ParallelTensor {
 public:

        "Unparseable AttrValue proto passed to "
        "TF_FunctionSetAttrValueProto");
    return;
  }

  auto fdef_or = func->record->mutable_fdef();
  if (!fdef_or.ok()) {
    status->status = fdef_or.status();
    return;
  }

  (*(fdef_or.value()->mutable_attr()))[string(attr_name)] = attr_value;

  status->status = absl::OkStatus();
}

  // version for the thread.
  StatusPtr status_ TF_GUARDED_BY(execution_mutex_);

  const std::string device_;
  ExecutorPtr executor_ TF_GUARDED_BY(execution_mutex_);
  mutable OpPtr op_ TF_GUARDED_BY(execution_mutex_);
  std::unique_ptr<Thread> thread_;
};

DeviceThread::~DeviceThread() {
  {
    tensorflow::mutex_lock l(execution_mutex_);

  // Another renaming of local device
  const string second_name = "def";
  server_def.set_job_name(second_name);
  server_def.mutable_cluster()->mutable_job(0)->set_name(second_name);
  (*server_def.mutable_cluster()->mutable_job(0)->mutable_tasks())[0] =
      absl::StrCat(second_name, ":",
                   tensorflow::testing::PickUnusedPortOrDie());

  serialized = server_def.SerializeAsString();