在Tensorflow数据集改组中BUFFER

本文介绍了在Tensorflow数据集改组中BUFFER_SIZE做什么?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

因此，我一直在使用以下代码: www.tensorflow/tutorials/generative/dcgan ，并且已经对其功能进行了很好的构思.但是，我不太了解 BUFFER_SIZE 变量的用途.我怀疑可以将其用于创建大小为 BUFFER_SIZE 的数据库的子集，然后从该子集中获取批处理，但是我看不到要点，也找不到人解释它.

So I've been play around with this code: www.tensorflow/tutorials/generative/dcgan and have almost developed a good idea about its functioning. However, I can't quite discover what is the BUFFER_SIZE variable's use. I suspect that it may be used to create a subset of the database of size BUFFER_SIZE and then the batches are taken from this subset, but I don't see the point on it and neither can find someone explaining it.

因此，如果有人可以向我解释 BUFFER_SIZE 的工作，我将很感激❤

So, if someone could explain me what BUFFER_SIZE does, I would be thankful ❤

推荐答案

它用作 tf.data.Dataset.shuffle 中的 buffer_size 参数.您是否阅读过文档?

It's used as the buffer_size argument in tf.data.Dataset.shuffle. Have you read the docs?

此数据集使用 buffer_size 元素填充缓冲区，然后从该缓冲区中随机采样元素，将所选元素替换为新元素.为了实现完美的改组，要求缓冲区大小大于或等于数据集的完整大小.

This dataset fills a buffer with buffer_size elements, then randomly samples elements from this buffer, replacing the selected elements with new elements. For perfect shuffling, a buffer size greater than or equal to the full size of the dataset is required.

例如，如果您的数据集包含10,000个元素，但 buffer_size 设置为1,000，则shuffle最初将仅从缓冲区的前1,000个元素中选择一个随机元素.选择一个元素后，其缓冲区中的空间将被下一个(即第1,001个)元素替换，并保留1,000个元素的缓冲区.

For instance, if your dataset contains 10,000 elements but buffer_size is set to 1,000, then shuffle will initially select a random element from only the first 1,000 elements in the buffer. Once an element is selected, its space in the buffer is replaced by the next (i.e. 1,001-st) element, maintaining the 1,000 element buffer.