a1c56a859e
* initial fastpair implementation * FastPair initial implementation * implement fastpair * Add random test * Add bench for fastpair * Refactor with constructor for FastPair * Add serialization for PairwiseDistance * Add fp_bench feature for fastpair bench
57 lines
1.9 KiB
Rust
57 lines
1.9 KiB
Rust
use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion};
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// to run this bench you have to change the declaraion in mod.rs ---> pub mod fastpair;
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use smartcore::algorithm::neighbour::fastpair::FastPair;
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use smartcore::linalg::naive::dense_matrix::*;
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use std::time::Duration;
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fn closest_pair_bench(n: usize, m: usize) -> () {
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let x = DenseMatrix::<f64>::rand(n, m);
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let fastpair = FastPair::new(&x);
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let result = fastpair.unwrap();
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result.closest_pair();
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}
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fn closest_pair_brute_bench(n: usize, m: usize) -> () {
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let x = DenseMatrix::<f64>::rand(n, m);
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let fastpair = FastPair::new(&x);
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let result = fastpair.unwrap();
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result.closest_pair_brute();
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}
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fn bench_fastpair(c: &mut Criterion) {
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let mut group = c.benchmark_group("FastPair");
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// with full samples size (100) the test will take too long
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group.significance_level(0.1).sample_size(30);
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// increase from default 5.0 secs
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group.measurement_time(Duration::from_secs(60));
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for n_samples in [100_usize, 1000_usize].iter() {
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for n_features in [10_usize, 100_usize, 1000_usize].iter() {
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"fastpair --- n_samples: {}, n_features: {}",
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n_samples, n_features
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)),
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n_samples,
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|b, _| b.iter(|| closest_pair_bench(*n_samples, *n_features)),
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);
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group.bench_with_input(
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BenchmarkId::from_parameter(format!(
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"brute --- n_samples: {}, n_features: {}",
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n_samples, n_features
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)),
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n_samples,
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|b, _| b.iter(|| closest_pair_brute_bench(*n_samples, *n_features)),
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);
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}
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}
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group.finish();
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}
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criterion_group!(benches, bench_fastpair);
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criterion_main!(benches);
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