Deep learning in Rust! This is my first shot at this. It's mostly just a proof of concept right now. The API will change.
We have these models implemented (check out the examples folder):
- MNIST handwritten digit recognition
- char-rnn using LSTM
So far, we have the following layers implemented:
- Matrix multiply (fully connected)
- Add (for bias, for example)
- LSTM
- Softmax
- MSE loss
- Cross entropy loss
We have the following optimizers:
- SGD
- RMSProp
- More layer types (in the order that I'll probably get to them)
- Conv2d
- Pooling
- Dropout
- Allow datatypes other than
f32
and implement casting between arrays of primitive numeric types. - Provide utilities for working with data
- images
- tsv and csv
- raw text data and word embeddings
We have a looong way to go :)
- Fast
- Easy to use
- Portable
- More control when you need it
- Easy to define custom layers
- Readable internal codebase
MIT