namespace tensorflow {

Status QueueRunner::New(const QueueRunnerDef& queue_runner_def,
                        std::unique_ptr<QueueRunner>* result) {
  result->reset(new QueueRunner());
  return (*result)->Init(queue_runner_def);
}

Status QueueRunner::New(const QueueRunnerDef& queue_runner_def,
                        Coordinator* coord,
                        std::unique_ptr<QueueRunner>* result) {
  result->reset(new QueueRunner());

#include "tensorflow/core/public/session.h"

namespace tensorflow {

/// QueueRunner class imitates the behavior of the python version of QueueRunner
/// which creates a thread for each enqueue op, runs close op on completion.
class QueueRunner : public RunnerInterface {
 public:
  /// Creates a new QueueRunner from proto.
  // TODO(yuefengz): we may want to initialize from queues and ops in the
  // future.

                          {Code::OUT_OF_RANGE, Code::CANCELLED});

  Coordinator coord;
  std::unique_ptr<QueueRunner> qr0;
  TF_EXPECT_OK(QueueRunner::New(queue_runner0, &coord, &qr0));
  TF_CHECK_OK(qr0->Start(session.get()));
  std::unique_ptr<QueueRunner> qr1;
  TF_EXPECT_OK(QueueRunner::New(queue_runner1, &coord, &qr1));
  TF_CHECK_OK(qr1->Start(session.get()));

/// otherwise the QueueRunner::Join() could sometimes hang. The
/// Coordinator::RequestStop() plays the key role which notifies all running
/// threads under a coordinator to stop. This function could be called by any
/// thread or any client.
/// Usage, in the client:
///   Coordinator coord;
///   std::unique_ptr<QueueRunner> qr(&coord, ...);
///   qr.Start(session);