neuramethyst

Author	SHA1	Message	Date
Shad Amethyst	a5237a8ef1	✨ Inefficient but working forward-forward implementation	2 years ago
Shad Amethyst	0c97a65013	🎨 Remove From<f64> requirement in dropout, working bivariate layer, add builder pattern	2 years ago
Shad Amethyst	9b821b92b0	🎨 Clean up NeuraSequential	2 years ago
Shad Amethyst	2edbff860c	🔥 🚚 ♻️ Refactoring the previous layer system It was becoming almost impossible to manage the dimensions of the layers, especially with convolution layers. Generic consts are nice, but they are a bit too early to have right now for this use-case. We'll probably be expanding the implementations to accept const or dynamically-sized layers at some point, for performance-critical applications.	2 years ago
Shad Amethyst	6c1d6874d7	♻️ Implement and transition to NeuraMatrix and NeuraVector, to prevent stack overflows	2 years ago
Shad Amethyst	920bca4a48	🚚 Move files and traits around, extract stuff out of train.rs	2 years ago
Shad Amethyst	b4a97694a6	🎨 Clean things up, add unit tests, add one hot layer	2 years ago
Shad Amethyst	bca56a5557	✨ Re-order arguments of neura_layer, implement softmax and normalization	2 years ago
Shad Amethyst	8ac82e20e2	✨ Working backpropagation :3	2 years ago
Shad Amethyst	7a6921a1c1	✨ 🔥 Semi-working training, although it seems to be only want to converge to zero	2 years ago