1 unstable release
0.1.0 | May 16, 2022 |
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#927 in Algorithms
Used in gosh-optim
140KB
2K
SLoC
LBFGS
Fast and safe Rust implementation of LBFGS and OWL-QN algorithms ported from Naoaki Okazaki's C library libLBFGS.
Check rust-liblbfgs for a working wrapper around the original C codes.
Motivation
- Bring native LBFGS implementation to Rust community.
- Learn how a great optimization algorithm is implemented in real world.
- Learn how to "replace the jet engine while still flying" URL
- Make it more maintainable with Rust high level abstraction.
- Improve it to meet my needs for computational chemistry.
Todo
- Parallel with rayon
- SIMD support
- add option to disable line search for gradient only optimization
- Fix issues inherited from liblbfgs URL
Features
- Clean and safe Rust implementation.
- OWL-QN algorithm.
- Closure based callback interfaces.
- Damped L-BFGS algorithm.
Usage
// 0. Import the lib
use liblbfgs::lbfgs;
const N: usize = 100;
// 1. Initialize data
let mut x = [0.0 as f64; N];
for i in (0..N).step_by(2) {
x[i] = -1.2;
x[i + 1] = 1.0;
}
// 2. Defining how to evaluate function and gradient
let evaluate = |x: &[f64], gx: &mut [f64]| {
let n = x.len();
let mut fx = 0.0;
for i in (0..n).step_by(2) {
let t1 = 1.0 - x[i];
let t2 = 10.0 * (x[i + 1] - x[i] * x[i]);
gx[i + 1] = 20.0 * t2;
gx[i] = -2.0 * (x[i] * gx[i + 1] + t1);
fx += t1 * t1 + t2 * t2;
}
Ok(fx)
};
let prb = lbfgs()
.with_max_iterations(5)
.with_orthantwise(1.0, 0, 99) // enable OWL-QN
.minimize(
&mut x, // input variables
evaluate, // define how to evaluate function
|prgr| { // define progress monitor
println!("iter: {:}", prgr.niter);
false // returning true will cancel optimization
}
)
.expect("lbfgs owlqn minimize");
println!("fx = {:}", prb.fx);
The callback functions are native Rust FnMut closures, possible to capture/change variables in the environment.
Full codes with comments are available in examples/sample.rs.
Run the example:
cargo run --example sample
Dependencies
~8–19MB
~282K SLoC