Deeplearning4j中的纪元和迭代

本文介绍了Deeplearning4j中的纪元和迭代的处理方法，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

我最近开始学习Deeplearning4j，但我不明白纪元和迭代的概念是如何实际实现的。
在在线文档中说：

I recently started learning Deeplearning4j and I fail to understand how the concept of epochs and iterations is actually implemented.In the online documentation it says:

我使用MultipleEpochsIterator进行了训练，但是对于第一次运行，我设置了1个历元，miniBatchSize = 1和1000个样本的数据集，因此我希望训练在1个历元和1000次迭代后完成，但是经过100.000次迭代后

I ran a training using a MultipleEpochsIterator, but for the first run I set 1 epoch, miniBatchSize = 1 and a dataset of 1000 samples, so I expected the training to finish after 1 epoch and 1000 iterations, but after more than 100.000 iterations it was still running.

int nEpochs = 1;
int miniBatchSize = 1;

MyDataSetFetcher fetcher = new MyDataSetFetcher(xDataDir, tDataDir, xSamples, tSamples);
//The same batch size set here was set in the model
BaseDatasetIterator baseIterator = new BaseDatasetIterator(miniBatchSize, sampleSize, fetcher);

MultipleEpochsIterator iterator = new MultipleEpochsIterator(nEpochs, baseIterator);
model.fit(iterator)

然后我做了更多的测试来改变批量大小，但是并没有改变IterationListener打印的日志行的频率。我的意思是我以为，如果将批次大小增加到100，那么使用1000个样本，我将仅更新10次参数，因此仅进行10次迭代，但是日志和时间戳记间隔大致相同。

Then I did more tests changing the batch size, but that didn't change the frequency of the log lines printed by the IterationListener. I mean that I thought that if I increase the batch size to 100 then with 1000 samples I would have just 10 updates of the parameters an therefore just 10 iterations, but the logs and the timestamp intervals are more or less the same.

BTW。有一个类似的问题，但答案实际上并未回答我的问题，我想更好地理解实际详细信息：

BTW. There is a similar question, but the answer does not actually answer my question, I would like to understand better the actual details:Deeplearning4j: Iterations, Epochs, and ScoreIterationListener

the

Deeplearning4j中的纪元和迭代

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