int64_t init_timeout_in_ms);

tensorflow::ServerDef ReplaceTaskInServerDef(
    const tensorflow::ServerDef& server_def, int task_index);

void ReplaceTaskInServerDef(tensorflow::ServerDef* server_def, int task_index,
                            const std::string& host, int port);

std::vector<std::string> ListDeviceNames(TFE_Context* ctx);

  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, proto_len)) {
    status->status = tensorflow::errors::InvalidArgument(
        "Invalid tensorflow.ServerDef protocol buffer");
    return;
  }
  status->status =
      tensorflow::unwrap(ctx)
          ->GetDistributedManager()
          ->InitializeLocalOnlyContext(server_def, keep_alive_secs);

	switch x := x.(type) {
	case *ast.Expr:
		switch (*x).(type) {
		case *ast.SelectorExpr:
			f.saveRef(x, context)
		}
	case *ast.CallExpr:
		f.saveCall(x, context)
	}
}

// Save references to C.xxx for later processing.
func (f *File) saveRef(n *ast.Expr, context astContext) {
	sel := (*n).(*ast.SelectorExpr)
	// For now, assume that the only instance of capital C is when

  // all tasks in the cluster.
  // This call internally coordinates with other tasks to initialize the eager
  // context and TF server for multi-client execution.
  virtual Status EnableCollectiveOps(const ServerDef& server_def) = 0;

  // Set a distributed manager that helps set up, update, and check liveness
  // of member tasks in the cluster.
  virtual void SetDistributedManager(

      freeze_checkpoint: If provided, run freeze_graph with this checkpoint to
        convert variables into constants.
      freeze_saver: If provided, run freeze_graph with this saver, in SaverDef
        binary form, to convert variables into constants.
      cpp_class: The name of the generated C++ class, wrapping the generated
        function.  The syntax of this flag is

// overhead and copies.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandleFromScalar(
    TF_DataType data_type, void* data, size_t len, TF_Status* status);

// Specify the server_def that enables collective ops.
// This is different to the above function in that it doesn't create remote
// contexts, and remotely executing ops is not possible. It just enables
// communication for collective ops.

                s: "3"
              }
            }
          }
        }
      }
    }
    versions {
      producer: 1520
      min_consumer: 12
    }
  }
  saver_def {
    filename_tensor_name: "saver_filename:0"
    save_tensor_name: "StatefulPartitionedCall:0"
    restore_op_name: "StatefulPartitionedCall_1"
    version: V2
  }
  collection_def {

}

tensorflow::ServerDef GetClusterServerDef(const string& worker_job_name,
                                          int num_workers) {
  tensorflow::ServerDef server_def = GetServerDef(worker_job_name, num_workers);
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();

  // Add a client.
  tensorflow::JobDef* job_def2 = cluster_def->add_job();
  job_def2->set_name("client");

#else
  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, static_cast<int>(proto_len))) {
    status->status = InvalidArgument(
        "Could not parse provided bytes into a ServerDef protocol buffer");
    return nullptr;
  }

  std::unique_ptr<tensorflow::ServerInterface> out_server;
  status->status = tensorflow::NewServer(server_def, &out_server);