def __init__(self, manager, task_id, sub_ids=None, dry_run=False, resubmit=False):
		self.__manager = manager
		self.__task	= self.__manager.load_task(task_id)
		self.__sub_ids = sub_ids
		self.__dry_run = dry_run
		self.__resubmit = resubmit

		self.__logger = logging.getLogger('JSUB')
		if self.__sub_ids==None:
			self.__sub_ids=range(len(self.__task.data['jobvar']))

		self.__initialize_manager()
def update_model(model, disc_grads, gen_grads, disc_opt, gen_opt,
                 global_step, update_scale):
  """Update model with gradients."""

  disc_vars, gen_vars = model.get_variables()

  with tf.control_dependencies(gen_grads + disc_grads):
    disc_update_op = disc_opt.apply_gradients(
        zip(_scale_vars(update_scale, disc_grads),
            disc_vars))

    gen_update_op = gen_opt.apply_gradients(
        zip(_scale_vars(update_scale, gen_grads),
            gen_vars),
        global_step=global_step)

    update_op = tf.group([disc_update_op, gen_update_op])

  return update_op