why number of classes are not the same in train and test? about few-shot

[MasterWinston]

you can see the article“https://arxiv.org/pdf/1703.05175.pdf”，
Section 2.6，it said：

---

Episode composition A straightforward way to construct episodes, used in Vinyals et al. [29] and
Ravi and Larochelle [22], is to choose Nc classes and NS support points per class in order to match
the expected situation at test-time. That is, if we expect at test-time to perform 5-way classification
and 1-shot learning, then training episodes could be comprised of Nc = 5, NS = 1. We have found,
however, that it can be extremely beneficial to train with a higher Nc, or “way”, than will be used
at test-time. In our experiments, we tune the training Nc on a held-out validation set. Another
consideration is whether to match NS, or “shot”, at train and test-time. For prototypical networks,
we found that it is usually best to train and test with the same “shot” number.

I also don't understand the principle。。