__init__.py 文件源码

def monitored_queue(*tensors,
                    capacity,
                    metric_name="items_in_queue",
                    return_queue=False):
    queue = tf.FIFOQueue(capacity, dtypes(*tensors))
    collections.add_metric(queue.size(), metric_name)

    add_queue_runner(queue, [queue.enqueue(tensors)])

    if return_queue:
        return queue

    results = queue.dequeue()

    for tensor, result \
            in zip(tensors, results if isinstance(results, list) else [results]):
        result.set_shape(tensor.get_shape())

    return results