Sparse Goodness: How Selective Measurement Transforms Forward-Forward Learning

Create a toolkit for testing non-backpropagation training methods like Forward-Forward. Developers should be able to plug in custom 'goodness' functions to experiment with layer-wise training on lightweight models.

Suggested repo: fflib

"Break the backprop dependency: experiments in local layer-wise learning."

Estimated effort: 30h