2 releases
0.1.1 | Jun 11, 2024 |
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0.1.0 | Jun 9, 2024 |
#272 in Machine learning
25KB
288 lines
mynn
A hobbyist no-std neural network library.
Explaination
This is a small library (currently ~200 lines minus doc comments and helper macros) I initially created during my lunch break when I had attempted to represent the shape of a neural network in Rust's type system, the result was I was able to make all the vectors into fixed sized arrays and allow the neural network to be no-std and in theory usable on microcontroller and embedded platforms.
See this example of a pre-trained model approximating an XOR running on an ATtiny85.
Installation
Command line:
cargo add mynn
Cargo.toml:
mynn = "0.1.1"
To use f32
in all operations, supply the f32
flag:
mynn = { version = "0.1.1", features = ["f32"] }
Example
Short example approximates the output of a XOR gate.
use mynn::make_network;
use mynn::activations::SIGMOID;
fn main() {
let inputs = [[0.0, 0.0], [0.0, 1.0], [1.0, 0.0], [1.0, 1.0]];
let targets = [[0.0], [1.0], [1.0], [0.0]];
let mut network = make_network!(2, 3, 1);
network.train(0.5, inputs, targets, 10_000, &SIGMOID);
println!("0 and 0: {:?}", network.predict([0.0, 0.0], &SIGMOID));
println!("1 and 0: {:?}", network.predict([1.0, 0.0], &SIGMOID));
println!("0 and 1: {:?}", network.predict([0.0, 1.0], &SIGMOID));
println!("1 and 1: {:?}", network.predict([1.0, 1.0], &SIGMOID));
}
Dependencies
~655KB
~15K SLoC