Higher-level PyTorch APIs: a short introduction to PyTorch-Lightning

In recent years, the PyTorch community developed several different libraries and APIs on top of PyTorch. Notable examples include fastai (https://docs.fast.ai/), Catalyst (https://github.com/catalyst-team/catalyst), PyTorch Lightning (https://www.pytorchlightning.ai), (https://lightning-flash.readthedocs.io/en/latest/quickstart.html), and PyTorch-Ignite (https://github.com/pytorch/ignite).

In this section, we will explore PyTorch Lightning (Lightning for short), which is a widely used PyTorch library that makes training deep neural networks simpler by removing much of the boilerplate code. However, while Lightning’s focus lies in simplicity and flexibility, it also allows us to use many advanced features such as multi-GPU support and fast low-precision training, which you can learn about in the official documentation at https://pytorch-lightning.rtfd.io/en/latest/.

There is also a bonus introduction...