A simple machine learning toolset

Introduction

Install

Example

use auto_diff::tensor::Tensor;
use auto_diff::rand::RNG;
use auto_diff::op::{Linear, Op};
use auto_diff::var::{Module, mseloss};
use auto_diff::optim::{SGD, Optimizer};

fn main() {

    fn func(input: &Tensor) -> Tensor {
        input.matmul(&Tensor::from_vec_f32(&vec![2., 3.], &vec![2, 1]))
    }

    let N = 10;
    let mut m = Module::new();
    let mut rng = RNG::new();
    rng.set_seed(123);
    let x = rng.normal(&vec![N, 2], 0., 2.);

    let y = func(&x);
    let op = Linear::new(Some(2), Some(1), true);
    rng.normal_(op.weight(), 0., 1.);
    rng.normal_(op.bias(), 0., 1.);

    let linear = Op::new(Box::new(op));

    let input = m.var();
    let output = input.to(&linear);
    let label = m.var();

    let loss = mseloss(&output, &label);

    input.set(x);
    label.set(y);

    let mut opt = SGD::new(0.2);

    for i in 0..100 {
        m.forward();
        m.backward(-1.);

        println!("{}", loss.get().get_scale_f32());

        opt.step(&m);
    }

}

Dependence

install gfortran is openblas-src = "0.9" is used.