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 batch_norm(inputs, training, data_format, name=''):
  """Performs a batch normalization using a standard set of parameters."""
  # We set fused=True for a significant performance boost. See
  # https://www.tensorflow.org/performance/performance_guide#common_fused_ops
  return tf.compat.v1.layers.batch_normalization(
      inputs=inputs,
      axis=1 if data_format == 'channels_first' else 3,
      momentum=_BATCH_NORM_DECAY,
      epsilon=_BATCH_NORM_EPSILON,
      center=True,
      scale=True,
      training=training,
      fused=True,
      name=name)