numpy reshape 中的 -1 是什么意思? [英] What does -1 in numpy reshape mean?

问题描述

 I have a numpy array (A) of shape = (100000, 28, 28)
 I reshape it using A.reshape(-1, 28x28)

这在机器学习管道中非常常见.这是如何运作的 ?我一直不明白重塑中-1"的含义.

This is very common use in Machine learning pipelines. How does this work ? I have never understood the meaning of '-1' in reshape.

一个确切的问题是这个但没有确切的解释.任何答案请?

An exact question is this But no solid explanation. Any answers pls ?

推荐答案

这意味着，您通过 -1 传递的维度的大小正在被推断.因此，

It means, that the size of the dimension, for which you passed -1, is being inferred. Thus,

A.reshape(-1, 28*28)

意思是重塑A，使其第二维的尺寸为28*28，并计算出第一维的正确尺寸".

means, "reshape A so that its second dimension has a size of 28*28 and calculate the correct size of the first dimension".

查看重塑文档.

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