// on each underlying device.
//
// For example if `device_name` is
//   "/job:localhost/replica:0/task:0/device:CUSTOM:0"
// and `underlying_devices` is
//   {"/job:localhost/replica:0/task:0/device:GPU:0",
//    "/job:localhost/replica:0/task:0/device:GPU:1"}
// Then executing an operation on CUSTOM:0 will execute it on GPU:0 and GPU:1.
//

tensorflow::ServerDef GetServerDef(const tensorflow::string& job_name,
                                   int num_tasks);

// Create a ServerDef with job name "localhost" and add `num_tasks` tasks in it.
tensorflow::ServerDef GetServerDef(int num_tasks);

// Create a multi-client ServerDef with the given `job_name`, add `num_tasks`
// tasks and `num_virtual_gpus` virtual GPUs in it.

  // chosen for the operation by the device placement logic in the
  // executor. After that, the value returned by DeviceName will be a full
  // device name such as "/job:localhost/replica:0/task:0/device:GPU:1".
  virtual const string& DeviceName() const = 0;

  // Sets the operation device name.
  //
  // The given `name` must be parseable by DeviceNameUtils::ParseFullName, and

// Registers a custom device for use with eager execution.
//
// Eager operations may be placed on this device, e.g.  `with
// tf.device("CUSTOM"):` from Python if `device_name` for this call is
// "/job:localhost/replica:0/task:0/device:CUSTOM:0".
//
// The custom device defines copy operations for moving TensorHandles on and
// off, and an execution operation for named operations. Often execution will