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Comments (2)

sile avatar sile commented on June 18, 2024

Thank you for the feature request!
It sounds nice, so let me consider how to implement that this week.

from tpe.

sile avatar sile commented on June 18, 2024

Sorry for the delayed response.
I added TpeOptimizer::trials method which can be used for this purpose (see an example below).

let temp_file = tempfile::NamedTempFile::new()?;
let mut rng = rand::thread_rng();

fn objective(x: f64) -> f64 {
    x.powi(2)
}

{
    let mut optim =
        tpe::TpeOptimizer::new(tpe::parzen_estimator(), tpe::range(-5.0, 5.0)?);

    // Runs 100 trials.
    for _ in 0..100 {
        let x = optim.ask(&mut rng)?;
        let v = objective(x);
        optim.tell(x, v)?;
    }

    // Stores the trials.
    let mut file = std::fs::OpenOptions::new()
        .write(true)
        .open(temp_file.path())?;
    serde_json::to_writer(&mut file, &optim.trials().collect::<Vec<_>>())?;
}

{
    let mut optim =
        tpe::TpeOptimizer::new(tpe::parzen_estimator(), tpe::range(-5.0, 5.0)?);

    // Loads the previous trials.
    let mut file = std::fs::File::open(temp_file.path())?;
    let trials: Vec<(f64, f64)> = serde_json::from_reader(&mut file)?;
    for (x, v) in trials {
        optim.tell(x, v)?;
    }

    // Runs additional 100 trials.
    for _ in 0..100 {
        let x = optim.ask(&mut rng)?;
        let v = objective(x);
        optim.tell(x, v)?;
    }
    assert_eq!(optim.trials().count(), 200);
}

from tpe.

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