Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'
This commit is contained in:
ruv
213
vendor/ruvector/crates/rvf/rvf-federation/benches/federation_bench.rs
vendored
Normal file
213
vendor/ruvector/crates/rvf/rvf-federation/benches/federation_bench.rs
vendored
Normal file
@@ -0,0 +1,213 @@
|
||||
//! Benchmarks for rvf-federation crate.
|
||||
|
||||
use criterion::{criterion_group, criterion_main, Criterion, black_box};
|
||||
use rvf_federation::*;
|
||||
use rvf_federation::aggregate::{FederatedAggregator, AggregationStrategy, Contribution};
|
||||
use rvf_federation::diff_privacy::{DiffPrivacyEngine, PrivacyAccountant};
|
||||
use rvf_federation::pii_strip::PiiStripper;
|
||||
use rvf_federation::federation::{ExportBuilder, ImportMerger};
|
||||
use rvf_federation::policy::FederationPolicy;
|
||||
|
||||
fn bench_pii_strip(c: &mut Criterion) {
|
||||
let mut group = c.benchmark_group("pii_strip");
|
||||
|
||||
group.bench_function("detect_mixed_pii", |b| {
|
||||
let stripper = PiiStripper::new();
|
||||
let input = "file at /home/alice/project/main.rs, ip 192.168.1.100, email alice@example.com, key sk-abcdefghijklmnopqrstuv12";
|
||||
b.iter(|| {
|
||||
black_box(stripper.contains_pii(black_box(input)));
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("strip_10_fields", |b| {
|
||||
let fields: Vec<(&str, &str)> = (0..10).map(|i| {
|
||||
if i % 3 == 0 {
|
||||
("path", "/home/user/data/file.csv")
|
||||
} else if i % 3 == 1 {
|
||||
("ip", "server at 10.0.0.1:8080")
|
||||
} else {
|
||||
("clean", "no pii here at all")
|
||||
}
|
||||
}).collect();
|
||||
b.iter(|| {
|
||||
let mut stripper = PiiStripper::new();
|
||||
black_box(stripper.strip_fields(black_box(&fields)));
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("strip_100_fields", |b| {
|
||||
let fields: Vec<(&str, &str)> = (0..100).map(|i| {
|
||||
if i % 5 == 0 {
|
||||
("path", "/home/user/data/file.csv")
|
||||
} else {
|
||||
("clean", "just normal text content")
|
||||
}
|
||||
}).collect();
|
||||
b.iter(|| {
|
||||
let mut stripper = PiiStripper::new();
|
||||
black_box(stripper.strip_fields(black_box(&fields)));
|
||||
});
|
||||
});
|
||||
|
||||
group.finish();
|
||||
}
|
||||
|
||||
fn bench_diff_privacy(c: &mut Criterion) {
|
||||
let mut group = c.benchmark_group("diff_privacy");
|
||||
|
||||
group.bench_function("gaussian_noise_100_params", |b| {
|
||||
b.iter(|| {
|
||||
let mut engine = DiffPrivacyEngine::gaussian(1.0, 1e-5, 1.0, 10.0).unwrap().with_seed(42);
|
||||
let mut params: Vec<f64> = (0..100).map(|i| i as f64 * 0.01).collect();
|
||||
black_box(engine.add_noise(black_box(&mut params)));
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("gaussian_noise_10000_params", |b| {
|
||||
b.iter(|| {
|
||||
let mut engine = DiffPrivacyEngine::gaussian(1.0, 1e-5, 1.0, 10.0).unwrap().with_seed(42);
|
||||
let mut params: Vec<f64> = (0..10_000).map(|i| i as f64 * 0.0001).collect();
|
||||
black_box(engine.add_noise(black_box(&mut params)));
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("gradient_clipping_1000", |b| {
|
||||
let engine = DiffPrivacyEngine::gaussian(1.0, 1e-5, 1.0, 1.0).unwrap();
|
||||
b.iter(|| {
|
||||
let mut grads: Vec<f64> = (0..1000).map(|i| (i as f64).sin()).collect();
|
||||
engine.clip_gradients(black_box(&mut grads));
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("privacy_accountant_100_rounds", |b| {
|
||||
b.iter(|| {
|
||||
let mut acc = PrivacyAccountant::new(100.0, 1e-5);
|
||||
for _ in 0..100 {
|
||||
acc.record_gaussian(1.0, 1.0, 1e-5, 100);
|
||||
}
|
||||
black_box(acc.current_epsilon());
|
||||
});
|
||||
});
|
||||
|
||||
group.finish();
|
||||
}
|
||||
|
||||
fn bench_aggregation(c: &mut Criterion) {
|
||||
let mut group = c.benchmark_group("aggregation");
|
||||
|
||||
group.bench_function("fedavg_10_contributors_100_dim", |b| {
|
||||
b.iter(|| {
|
||||
let mut agg = FederatedAggregator::new("test".into(), AggregationStrategy::FedAvg)
|
||||
.with_min_contributions(2);
|
||||
for i in 0..10 {
|
||||
agg.add_contribution(Contribution {
|
||||
contributor: format!("c_{}", i),
|
||||
weights: (0..100).map(|j| (i as f64 + j as f64) * 0.01).collect(),
|
||||
quality_weight: 0.8 + (i as f64) * 0.02,
|
||||
trajectory_count: 100 + i * 10,
|
||||
});
|
||||
}
|
||||
black_box(agg.aggregate().unwrap());
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("fedavg_100_contributors_1000_dim", |b| {
|
||||
b.iter(|| {
|
||||
let mut agg = FederatedAggregator::new("test".into(), AggregationStrategy::FedAvg)
|
||||
.with_min_contributions(2);
|
||||
for i in 0..100 {
|
||||
agg.add_contribution(Contribution {
|
||||
contributor: format!("c_{}", i),
|
||||
weights: (0..1000).map(|j| (i as f64 + j as f64) * 0.001).collect(),
|
||||
quality_weight: 0.8,
|
||||
trajectory_count: 100,
|
||||
});
|
||||
}
|
||||
black_box(agg.aggregate().unwrap());
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("byzantine_detection_50_contributors", |b| {
|
||||
b.iter(|| {
|
||||
let mut agg = FederatedAggregator::new("test".into(), AggregationStrategy::FedAvg)
|
||||
.with_min_contributions(2)
|
||||
.with_byzantine_threshold(2.0);
|
||||
for i in 0..48 {
|
||||
agg.add_contribution(Contribution {
|
||||
contributor: format!("good_{}", i),
|
||||
weights: vec![1.0; 50],
|
||||
quality_weight: 0.9,
|
||||
trajectory_count: 100,
|
||||
});
|
||||
}
|
||||
// Add 2 outliers
|
||||
agg.add_contribution(Contribution {
|
||||
contributor: "evil_1".to_string(),
|
||||
weights: vec![1000.0; 50],
|
||||
quality_weight: 0.9,
|
||||
trajectory_count: 100,
|
||||
});
|
||||
agg.add_contribution(Contribution {
|
||||
contributor: "evil_2".to_string(),
|
||||
weights: vec![-500.0; 50],
|
||||
quality_weight: 0.9,
|
||||
trajectory_count: 100,
|
||||
});
|
||||
black_box(agg.aggregate().unwrap());
|
||||
});
|
||||
});
|
||||
|
||||
group.finish();
|
||||
}
|
||||
|
||||
fn bench_export_import(c: &mut Criterion) {
|
||||
let mut group = c.benchmark_group("export_import");
|
||||
|
||||
group.bench_function("full_export_pipeline", |b| {
|
||||
b.iter(|| {
|
||||
let mut dp = DiffPrivacyEngine::gaussian(1.0, 1e-5, 1.0, 10.0).unwrap().with_seed(42);
|
||||
let priors = TransferPriorSet {
|
||||
source_domain: "/home/user/my_domain".to_string(),
|
||||
entries: (0..20).map(|i| TransferPriorEntry {
|
||||
bucket_id: format!("bucket_{}", i),
|
||||
arm_id: format!("arm_{}", i % 4),
|
||||
params: BetaParams::new(5.0 + i as f64, 3.0 + i as f64 * 0.5),
|
||||
observation_count: 50 + i * 10,
|
||||
}).collect(),
|
||||
cost_ema: 0.85,
|
||||
};
|
||||
let export = ExportBuilder::new("pseudo".into(), "domain".into())
|
||||
.add_priors(priors)
|
||||
.add_weights((0..256).map(|i| i as f64 * 0.001).collect())
|
||||
.add_string_field("note".into(), "trained on /home/user/data at 192.168.1.1".into())
|
||||
.build(&mut dp)
|
||||
.unwrap();
|
||||
black_box(export);
|
||||
});
|
||||
});
|
||||
|
||||
group.bench_function("merge_100_priors", |b| {
|
||||
let merger = ImportMerger::new();
|
||||
let remote: Vec<TransferPriorEntry> = (0..100).map(|i| TransferPriorEntry {
|
||||
bucket_id: format!("bucket_{}", i),
|
||||
arm_id: format!("arm_{}", i % 4),
|
||||
params: BetaParams::new(10.0, 5.0),
|
||||
observation_count: 50,
|
||||
}).collect();
|
||||
b.iter(|| {
|
||||
let mut local: Vec<TransferPriorEntry> = (0..50).map(|i| TransferPriorEntry {
|
||||
bucket_id: format!("bucket_{}", i),
|
||||
arm_id: format!("arm_{}", i % 4),
|
||||
params: BetaParams::new(5.0, 3.0),
|
||||
observation_count: 20,
|
||||
}).collect();
|
||||
merger.merge_priors(black_box(&mut local), black_box(&remote), 1);
|
||||
black_box(local);
|
||||
});
|
||||
});
|
||||
|
||||
group.finish();
|
||||
}
|
||||
|
||||
criterion_group!(benches, bench_pii_strip, bench_diff_privacy, bench_aggregation, bench_export_import);
|
||||
criterion_main!(benches);
|
||||
Reference in New Issue
Block a user