Lightweight fork of the unda crate meant for running precompiled models on embedded systems
esp-idf-unda can be used to run precompiled ML models created by the unda crate. Creating a model in a Unda program and using the network.serialize_unda_fmt("out.unda"); will create a .unda file that is compatible with being deserialized by esp-idf-unda.
File IO support is soon to come, but as a quick proof of concept esp-idf-unda can currently parse neural network strings copied from the .unda file and perform forwards predictions.
let model_str = "D|3|2|10.845654 11.002682 -13.501029 -14.699452 -53.440483 -53.715294|
-6.101849 49.06853 61.28852#D|1|3|30.350481 -78.40228 70.861206|-19.532055#D|1|1|15.161753|-3.7315714".to_string();
let mut xor_net = Network::deserialize_unda_fmt_string(model_str);creates a simple Network based on a trained SIGMOID XoR predictor.
The .unda file format currently defaults to SIGMOID activations, but its a top priority to implement activation function support in this file format
If open source development is your thing, we at unda would love additional work on anything that can be implemented, please contact [email protected] if you'd like to help out!
Licensed under the Apache License, Version 2.0 http://www.apache.org/licenses/LICENSE-2.0 or the MIT license http://opensource.org/licenses/MIT, at your option. This file may not be copied, modified, or distributed except according to those terms.