• =caffe.rs= A Rust FFI wrapper for the [[http://caffe.berkeleyvision.org/][Caffe]] deep learning library, using [[https://github.com/crabtw/rust-bindgen][rust-bindgen]].

** Setup Requires a =caffe= distribution built with the patches in =ajtulloch/caffe:caffe-ffi= (https://github.com/ajtulloch/caffe/tree/caffe-ffi) to expose the necessary structures over FFI.

You can clone and build that repository as usual.

Note that to build and run the tests, you'll have to modify =src/ffi.rs= to point to the right location for your installation. To get the tests passing, update the dataset locations in =test-data/lenettraintest.prototxt=.

** Example

* Inference on a pre-trained network

+BEGIN_SRC rust

// Create the newtork let mut net = caffe::Net::new(Path::new("test-data/lenet.prototxt"), caffe::Phase::Test); // Initialize the weights net.copytrainedlayers_from(Path::new("test-data/lenet.caffemodel"));

// Fill in the input data blob. let mut datablob = net.blob("data"); let mut ones: Vec<_> = repeat(1.0 as f32) .take(datablob.len()) .collect(); datablob.setdata(ones.asmutslice());

// Run a foward pass. net.forwardprefilled(); let probblob = net.blob("prob");

// Process the output probabilities. let probs = probblob.asslice(); println!("{:?}", probs.tovec()); asserteq!(probs[0], 0.06494621)

+END_SRC

* Running a solver

+BEGIN_SRC rust

let mut solver = caffe::Solver::new( Path::new("test-data/lenet_solver.prototxt")); solver.solve();

+END_SRC