Python TensorFlow教程中的next_batch batch_xs,batch_ys = mnist.train.next_batch(100)从何而来？
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Where does next_batch in the TensorFlow tutorial batch_xs, batch_ys = mnist.train.next_batch(100) come from?
提问by Dan
I am trying out the TensorFlow tutorial and don't understand where does next_batch in this line come from?
我正在尝试 TensorFlow 教程，但不明白这一行中的 next_batch 来自哪里？
batch_xs, batch_ys = mnist.train.next_batch(100)
I looked at
我在看
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
And didn't see next_batch there either.
也没有在那里看到 next_batch 。
Now when trying out next_batch in my own code, I am getting
现在在我自己的代码中尝试 next_batch 时，我得到了
AttributeError: 'numpy.ndarray' object has no attribute 'next_batch'
So I would like to understand where does next_batch come from?
所以我想了解next_batch从哪里来？
回答by Nick Becker
next_batchis a method of the DataSetclass (see https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/learn/python/learn/datasets/mnist.pyfor more information on what's in the class).
next_batch是DataSet类的方法（有关类中内容的更多信息，请参见https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/learn/python/learn/datasets/mnist.py）。
When you load the mnist data and assign it to the variable mnistwith:
当您加载 mnist 数据并将其分配给变量mnist时：
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
look at the class of mnist.train. You can see it by typing:
看看班级mnist.train。您可以通过键入以下内容查看它：
print mnist.train.__class__
You'll see the following:
您将看到以下内容：
<class 'tensorflow.contrib.learn.python.learn.datasets.mnist.Dataset'>
Because mnist.trainis an instance of class DataSet, you can use the class's function next_batch. For more information on classes, check out the documentation.
因为mnist.train是 class 的一个实例DataSet，所以可以使用 class 的 function next_batch。有关类的更多信息，请查看文档。
回答by Dark Element
After looking through the tensorflow repository, it seems to originate here:
查看 tensorflow 存储库后，它似乎起源于这里：
However if you're looking to implement it in your own code (for your own dataset), it would likely be much simpler to write it yourself in a dataset object, as I did. As I understand it, it's a method to shuffle the entire dataset, and return $mini_batch_size number of samples from the shuffled dataset.
但是，如果您希望在您自己的代码中实现它（对于您自己的数据集），那么像我一样在数据集对象中自己编写它可能会简单得多。据我了解，这是一种对整个数据集进行混洗并从混洗数据集中返回 $mini_batch_size 样本数的方法。
Here's some pseudocode:
这是一些伪代码：
shuffle data.x and data.y while retaining relation
return [data.x[:mb_n], data.y[:mb_n]]
shuffle data.x and data.y while retaining relation
return [data.x[:mb_n], data.y[:mb_n]]
回答by Bright Chang
You can just use the help function:
您可以只使用帮助功能：
help(tf.contrib.learn.datasets.mnist.DataSet.next_batch)
and get the document of function next_batch
并获取函数 next_batch 的文档
