refactor(tests): split integration.rs into focused subfolders
- Delete 20 duplicate tests already covered by parameter_tests.rs - Move 11 pure Trial unit tests into src/trial.rs - Split remaining 84 integration tests into tests/study/ (9 modules) - Group sampler tests into tests/sampler/ (7 modules) - Group pruner tests into tests/pruner/ (2 modules)
This commit is contained in:
@@ -0,0 +1,189 @@
|
||||
use std::collections::HashMap;
|
||||
|
||||
use optimizer::parameter::{FloatParam, IntParam, ParamValue, Parameter};
|
||||
use optimizer::sampler::random::RandomSampler;
|
||||
use optimizer::{Direction, Error, Study};
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_params_evaluated_first() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
let y = IntParam::new(1, 100);
|
||||
|
||||
// Enqueue a specific configuration
|
||||
study.enqueue(HashMap::from([
|
||||
(x.id(), ParamValue::Float(5.0)),
|
||||
(y.id(), ParamValue::Int(42)),
|
||||
]));
|
||||
|
||||
// The first trial should use the enqueued params
|
||||
let mut trial = study.ask();
|
||||
let x_val = x.suggest(&mut trial).unwrap();
|
||||
let y_val = y.suggest(&mut trial).unwrap();
|
||||
|
||||
assert_eq!(x_val, 5.0);
|
||||
assert_eq!(y_val, 42);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_fifo_order() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
|
||||
// Enqueue two configs
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(1.0))]));
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(2.0))]));
|
||||
|
||||
// First trial gets first enqueued value
|
||||
let mut trial1 = study.ask();
|
||||
assert_eq!(x.suggest(&mut trial1).unwrap(), 1.0);
|
||||
|
||||
// Second trial gets second enqueued value
|
||||
let mut trial2 = study.ask();
|
||||
assert_eq!(x.suggest(&mut trial2).unwrap(), 2.0);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_then_normal_sampling_resumes() {
|
||||
let sampler = RandomSampler::with_seed(42);
|
||||
let study: Study<f64> = Study::with_sampler(Direction::Minimize, sampler);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
|
||||
// Enqueue one config
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(5.0))]));
|
||||
|
||||
// First trial uses enqueued value
|
||||
let mut trial1 = study.ask();
|
||||
assert_eq!(x.suggest(&mut trial1).unwrap(), 5.0);
|
||||
study.tell(trial1, Ok::<_, &str>(25.0));
|
||||
|
||||
// Second trial uses normal sampling (not 5.0)
|
||||
let mut trial2 = study.ask();
|
||||
let x_val = x.suggest(&mut trial2).unwrap();
|
||||
// The sampled value should be in [0, 10] but extremely unlikely to be exactly 5.0
|
||||
assert!((0.0..=10.0).contains(&x_val));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_with_optimize() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
|
||||
// Enqueue two specific configs
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(1.0))]));
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(2.0))]));
|
||||
|
||||
let mut values = Vec::new();
|
||||
|
||||
study
|
||||
.optimize(5, |trial| {
|
||||
let x_val = x.suggest(trial)?;
|
||||
values.push(x_val);
|
||||
Ok::<_, Error>(x_val * x_val)
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
// First two trials should use enqueued values
|
||||
assert_eq!(values[0], 1.0);
|
||||
assert_eq!(values[1], 2.0);
|
||||
// All 5 trials should have completed
|
||||
assert_eq!(study.n_trials(), 5);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_partial_params_fall_back_to_sampling() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
let y = IntParam::new(1, 100);
|
||||
|
||||
// Enqueue only x, not y
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(3.0))]));
|
||||
|
||||
let mut trial = study.ask();
|
||||
let x_val = x.suggest(&mut trial).unwrap();
|
||||
let y_val = y.suggest(&mut trial).unwrap();
|
||||
|
||||
// x should be the enqueued value
|
||||
assert_eq!(x_val, 3.0);
|
||||
// y should be sampled (within range)
|
||||
assert!((1..=100).contains(&y_val));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_trials_appear_in_completed_trials() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(7.0))]));
|
||||
|
||||
study
|
||||
.optimize(1, |trial| {
|
||||
let x_val = x.suggest(trial)?;
|
||||
Ok::<_, Error>(x_val)
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
let trials = study.trials();
|
||||
assert_eq!(trials.len(), 1);
|
||||
assert_eq!(trials[0].value, 7.0);
|
||||
assert_eq!(
|
||||
*trials[0].params.get(&x.id()).unwrap(),
|
||||
ParamValue::Float(7.0)
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_with_ask_and_tell() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(4.0))]));
|
||||
|
||||
let mut trial = study.ask();
|
||||
let x_val = x.suggest(&mut trial).unwrap();
|
||||
assert_eq!(x_val, 4.0);
|
||||
|
||||
study.tell(trial, Ok::<_, &str>(x_val * x_val));
|
||||
assert_eq!(study.n_trials(), 1);
|
||||
assert_eq!(study.best_value().unwrap(), 16.0);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_n_enqueued() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
|
||||
assert_eq!(study.n_enqueued(), 0);
|
||||
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(1.0))]));
|
||||
assert_eq!(study.n_enqueued(), 1);
|
||||
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(2.0))]));
|
||||
assert_eq!(study.n_enqueued(), 2);
|
||||
|
||||
// Creating a trial dequeues one
|
||||
let _ = study.ask();
|
||||
assert_eq!(study.n_enqueued(), 1);
|
||||
|
||||
let _ = study.ask();
|
||||
assert_eq!(study.n_enqueued(), 0);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_enqueue_counted_in_n_trials() {
|
||||
let study: Study<f64> = Study::new(Direction::Minimize);
|
||||
let x = FloatParam::new(0.0, 10.0);
|
||||
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(1.0))]));
|
||||
study.enqueue(HashMap::from([(x.id(), ParamValue::Float(2.0))]));
|
||||
|
||||
study
|
||||
.optimize(5, |trial| {
|
||||
let x_val = x.suggest(trial)?;
|
||||
Ok::<_, Error>(x_val)
|
||||
})
|
||||
.unwrap();
|
||||
|
||||
// All 5 trials count, including the 2 enqueued ones
|
||||
assert_eq!(study.n_trials(), 5);
|
||||
}
|
||||
Reference in New Issue
Block a user