Manuel Raimann
ee59c9cdd0
- Split pruning_and_callbacks into pruning and early_stopping - Split advanced_features into async_parallel, journal_storage, ask_and_tell, multi_objective - Each example now requires only its own feature flag - Trim sampler_comparison winner logic and verbose header - Update CI workflow and README to match new example names
52 lines
1.5 KiB
Rust
52 lines
1.5 KiB
Rust
//! Ask-and-tell interface — decouple sampling from evaluation.
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//!
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//! Use `ask()` to get a trial with sampled parameters, evaluate it however
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//! you like (workers, GPUs, external processes), then `tell()` the result.
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//! This is useful for batch evaluation or custom scheduling.
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//!
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//! Run with: `cargo run --example ask_and_tell`
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use optimizer::prelude::*;
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fn main() -> optimizer::Result<()> {
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let study: Study<f64> = Study::new(Direction::Minimize);
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let x = FloatParam::new(-5.0, 5.0).name("x");
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let y = FloatParam::new(-5.0, 5.0).name("y");
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for batch in 0..3 {
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let batch_size = 5;
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let mut trials = Vec::with_capacity(batch_size);
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// ask() creates trials with sampled parameters
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for _ in 0..batch_size {
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let mut trial = study.ask();
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let xv = x.suggest(&mut trial)?;
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let yv = y.suggest(&mut trial)?;
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trials.push((trial, xv, yv));
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}
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// Evaluate the batch (could be sent to workers, GPUs, etc.)
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for (trial, xv, yv) in trials {
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let value = xv * xv + yv * yv;
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study.tell(trial, Ok::<_, &str>(value));
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}
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println!(
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"Batch {}: evaluated {batch_size} trials (total: {})",
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batch + 1,
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study.n_trials(),
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);
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}
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let best = study.best_trial()?;
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println!(
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"Best: f({:.3}, {:.3}) = {:.6}",
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best.get(&x).unwrap(),
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best.get(&y).unwrap(),
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best.value,
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);
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Ok(())
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}
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