feat: add Pruner trait and NopPruner default implementation

Introduce the pruning extension point for the trial pruning system.
The Pruner trait allows deciding whether to stop a trial early based
on intermediate values. NopPruner (never prunes) is the default.
This commit is contained in:
Manuel Raimann
2026-02-11 15:46:56 +01:00
parent d88280c152
commit 2651e61b2c
4 changed files with 138 additions and 0 deletions
+3
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@@ -188,6 +188,7 @@ mod error;
mod kde;
mod param;
pub mod parameter;
pub mod pruner;
pub mod sampler;
mod study;
mod trial;
@@ -200,6 +201,7 @@ pub use param::ParamValue;
pub use parameter::{
BoolParam, Categorical, CategoricalParam, EnumParam, FloatParam, IntParam, ParamId, Parameter,
};
pub use pruner::{NopPruner, Pruner};
pub use sampler::CompletedTrial;
pub use sampler::grid::GridSearchSampler;
pub use sampler::random::RandomSampler;
@@ -222,6 +224,7 @@ pub mod prelude {
pub use crate::parameter::{
BoolParam, Categorical, CategoricalParam, EnumParam, FloatParam, IntParam, Parameter,
};
pub use crate::pruner::{NopPruner, Pruner};
pub use crate::sampler::CompletedTrial;
pub use crate::sampler::grid::GridSearchSampler;
pub use crate::sampler::random::RandomSampler;
+60
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@@ -0,0 +1,60 @@
//! Pruner trait and implementations for trial pruning.
//!
//! Pruners decide whether to stop (prune) a trial early based on its
//! intermediate values compared to other trials. This is useful for
//! discarding unpromising trials before they complete, saving compute.
mod nop;
pub use nop::NopPruner;
use crate::sampler::CompletedTrial;
/// Trait for pluggable trial pruning strategies.
///
/// Pruners are consulted after each intermediate value is reported to
/// decide whether the trial should be stopped early. The trait requires
/// `Send + Sync` to support concurrent and async optimization.
///
/// # Implementing a custom pruner
///
/// ```
/// use optimizer::pruner::Pruner;
/// use optimizer::sampler::CompletedTrial;
///
/// struct MyPruner {
/// threshold: f64,
/// }
///
/// impl Pruner for MyPruner {
/// fn should_prune(
/// &self,
/// _trial_id: u64,
/// _step: u64,
/// intermediate_values: &[(u64, f64)],
/// _completed_trials: &[CompletedTrial],
/// ) -> bool {
/// // Prune if the latest value exceeds the threshold
/// intermediate_values
/// .last()
/// .is_some_and(|&(_, v)| v > self.threshold)
/// }
/// }
/// ```
pub trait Pruner: Send + Sync {
/// Decide whether to prune a trial at the given step.
///
/// # Arguments
///
/// * `trial_id` - The current trial's ID.
/// * `step` - The step at which the intermediate value was reported.
/// * `intermediate_values` - All `(step, value)` pairs reported so far for this trial.
/// * `completed_trials` - History of all completed trials (for comparison).
fn should_prune(
&self,
trial_id: u64,
step: u64,
intermediate_values: &[(u64, f64)],
completed_trials: &[CompletedTrial],
) -> bool;
}
+17
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@@ -0,0 +1,17 @@
use super::Pruner;
use crate::sampler::CompletedTrial;
/// A pruner that never prunes. This is the default when no pruner is configured.
pub struct NopPruner;
impl Pruner for NopPruner {
fn should_prune(
&self,
_trial_id: u64,
_step: u64,
_intermediate_values: &[(u64, f64)],
_completed_trials: &[CompletedTrial],
) -> bool {
false
}
}
+58
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@@ -9,6 +9,7 @@ use std::sync::Arc;
use parking_lot::RwLock;
use crate::pruner::{NopPruner, Pruner};
use crate::sampler::random::RandomSampler;
use crate::sampler::{CompletedTrial, Sampler};
use crate::trial::Trial;
@@ -40,6 +41,8 @@ where
direction: Direction,
/// The sampler used to generate parameter values.
sampler: Arc<dyn Sampler>,
/// The pruner used to decide whether to stop trials early.
pruner: Arc<dyn Pruner>,
/// Completed trials (wrapped in Arc for sharing with Trial).
completed_trials: Arc<RwLock<Vec<CompletedTrial<V>>>>,
/// Counter for generating unique trial IDs.
@@ -109,6 +112,7 @@ where
Self {
direction,
sampler,
pruner: Arc::new(NopPruner),
completed_trials,
next_trial_id: AtomicU64::new(0),
trial_factory,
@@ -158,6 +162,46 @@ where
/// let mut study: Study<f64> = Study::new(Direction::Minimize);
/// study.set_sampler(TpeSampler::new());
/// ```
/// Creates a new study with a custom sampler and pruner.
///
/// # Arguments
///
/// * `direction` - Whether to minimize or maximize the objective function.
/// * `sampler` - The sampler to use for parameter sampling.
/// * `pruner` - The pruner to use for trial pruning.
///
/// # Examples
///
/// ```
/// use optimizer::pruner::NopPruner;
/// use optimizer::sampler::random::RandomSampler;
/// use optimizer::{Direction, Study};
///
/// let sampler = RandomSampler::with_seed(42);
/// let study: Study<f64> = Study::with_sampler_and_pruner(Direction::Minimize, sampler, NopPruner);
/// ```
pub fn with_sampler_and_pruner(
direction: Direction,
sampler: impl Sampler + 'static,
pruner: impl Pruner + 'static,
) -> Self
where
V: 'static,
{
let sampler: Arc<dyn Sampler> = Arc::new(sampler);
let completed_trials = Arc::new(RwLock::new(Vec::new()));
let trial_factory = Self::make_trial_factory(&sampler, &completed_trials);
Self {
direction,
sampler,
pruner: Arc::new(pruner),
completed_trials,
next_trial_id: AtomicU64::new(0),
trial_factory,
}
}
pub fn set_sampler(&mut self, sampler: impl Sampler + 'static)
where
V: 'static,
@@ -166,6 +210,20 @@ where
self.trial_factory = Self::make_trial_factory(&self.sampler, &self.completed_trials);
}
/// Sets a new pruner for the study.
///
/// # Arguments
///
/// * `pruner` - The pruner to use for trial pruning.
pub fn set_pruner(&mut self, pruner: impl Pruner + 'static) {
self.pruner = Arc::new(pruner);
}
/// Returns a reference to the study's pruner.
pub fn pruner(&self) -> &dyn Pruner {
&*self.pruner
}
/// Generates the next unique trial ID.
pub(crate) fn next_trial_id(&self) -> u64 {
self.next_trial_id.fetch_add(1, Ordering::SeqCst)