How to use lightning without any explicit train_dataloader?
❓ Questions and Help

What is your question?
I'm working on Neural Style Transfer (the original paper by Gatys et. al.). The method is essentially specific to one style and one content image only, which can be loaded in the __init__() method itself. And there's no other data set required (training or validation). Once we have the style and content images, we iteratively generate the stylized image (and the logic resides in training_step()).
However, Lightning requires at minimum to define a train_dataloader(). How should I move forward now? Should I create a dummy dataloader? Is there a recommended way to get around this?
What's your environment?

OS: Linux, Win
Packaging: conda
Version: 1.0.4