plan.py 文件源码

def _create_queue(self, queue_id, ctor=tf.RandomShuffleQueue):
    # The enqueuing workers transform inputs into serialized loom
    # weaver messages, which are represented as strings.
    return ctor(
        capacity=self.queue_capacity or 4 * self.batch_size,
        min_after_dequeue=0, dtypes=[tf.string], shapes=[tf.TensorShape([])],
        shared_name='tensorflow_fold_plan_queue%s' % queue_id)