Simple MNIST Example

[shatz01]

This mnist example is intended to be a friendly/approachable introduction to the core elements of fuse. Which is mostly our batch dict, ready-to-go datasets, and loss functions.

• Simplified Example
• Removed Eval/Test
• Added some defaults to LightningModuleDefault so that it can just be inherited from and user can set model and model dir themselves (looks cleaner imo)

Happy to add back some functionality if anyone wants. @mosheraboh @avihu111 @SagiPolaczek

[shatz01]

I think the added features like inference and evaluation are important to be shown somewhere, though not sure if mnist is the place. It depends on how expensive/annoying it is for us to "maintain" multiple training scripts for mnist and all of our other examples. If it costs us nothing, then I say we should just leave them. But if its even a little time consuming for us to maintain them, then I say at least for mnist we should get rid of the more complex scripts. Leave them for the more complex examples/datasets like knight and isic.

[YoelShoshan]

I wonder if and how much emphasis we should put into showing that pytorch-lightning can be used directly without any wrapping, as people already know pytorch-lightning well. This is the way that I use Fuse and find it very convenient and flexible.

Let's discuss this in our next design sessions.

We can call it "managed" vs. "unmanaged" :)

The disadvantage is that it adds some boilerplate code, the advantage is that it is more transparent and not hidden behind a class that is opaque for a newcomer

[shatz01]

@YoelShoshan I guess you are referring to the way that the model is constructed in the custom mnist example? https://github.com/BiomedSciAI/fuse-med-ml/blob/master/examples/fuse_examples/imaging/classification/mnist/run_mnist_custom_pl_imp.py

If so we can just replace the other mnist and leave this custom one.