bench(cogs): steady-state CPU infer latency benches (ADR-163 T2)
Criterion benches over InferenceEngine::infer for cog-person-count and cog-pose-estimation, on Device::Cpu with the real shipped safetensors weights (asserts candle backend so the stub is never silently benched), over a fixed CSI window after a warm-up forward. HOST-MEASURED steady-state medians (idle box): ~305us each. This is the recurring per-frame cost and is explicitly NOT the pose manifest's cold_start_ms_avg=5.4 (a different measurement, weight-load included, taken on ruvultra/RTX 5080) -- the two are labelled and not conflated. Closes the ADR-159/160 deferred cog inference-latency item. No production- code behavior change. Co-Authored-By: claude-flow <ruv@ruv.net>
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@ -1015,6 +1015,7 @@ dependencies = [
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"candle-core 0.9.2",
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"candle-nn 0.9.2",
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"clap",
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"criterion",
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"safetensors 0.4.5",
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"serde",
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"serde_json",
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@ -1034,6 +1035,7 @@ dependencies = [
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"candle-core 0.9.2",
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"candle-nn 0.9.2",
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"clap",
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"criterion",
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"hex",
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"safetensors 0.4.5",
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"serde",
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@ -34,6 +34,12 @@ safetensors = "0.4"
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[dev-dependencies]
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tempfile = "3"
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approx = "0.5"
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# ADR-163: steady-state infer latency bench (real count_v1 weights, Device::Cpu).
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criterion = { version = "0.5", features = ["html_reports"] }
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[[bench]]
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name = "infer_bench"
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harness = false
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[features]
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default = []
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@ -0,0 +1,95 @@
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//! Criterion bench for `cog-person-count` steady-state inference latency
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//! (ADR-163, closing the ADR-159/160 deferred "cog inference latency bench" item).
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//!
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//! ## What this measures — and what the manifest's `cold_start_ms` does NOT
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//!
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//! This benches **steady-state** `InferenceEngine::infer` over a FIXED CSI
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//! window on `Device::Cpu` with the **real** shipped `count_v1.safetensors`
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//! weights — i.e. the per-frame cost once the model is loaded and warm.
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//!
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//! The cog manifest's `build_metadata.cold_start_ms_avg` (in the pose cog;
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//! person-count's manifest carries comparable provenance) is a **DIFFERENT
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//! measurement**: it includes one-time weight load / mmap / first-forward
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//! allocation. Cold-start is a startup cost paid once; steady-state infer is the
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//! recurring per-frame cost. They are not comparable and we do not conflate them.
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//! `cold_start` was measured on ruvultra (RTX 5080 host, candle 0.9 cpu); this
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//! bench runs on whatever machine you run it on — see `benchmarks/edge-latency/RESULTS.md`
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//! for the host the committed numbers were taken on.
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//!
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//! If the weights file is absent the engine falls back to the zero-confidence
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//! stub; we skip the bench in that case rather than benchmark the stub (which
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//! would be a meaningless number) — the bench prints a notice and measures a
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//! no-op so criterion still produces a (clearly-labelled) datapoint.
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//!
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//! Run (cog crates are normal workspace members):
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//! cd v2 && cargo bench -p cog-person-count --no-default-features
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//! cd v2 && cargo bench -p cog-person-count --no-default-features -- --warm-up-time 1 --measurement-time 2
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use std::hint::black_box;
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use std::path::Path;
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use criterion::{criterion_group, criterion_main, Criterion};
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use cog_person_count::inference::{CsiWindow, InferenceEngine, INPUT_SUBCARRIERS, INPUT_TIMESTEPS};
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/// Deterministic fixed CSI window (seed-stable LCG), normalised-ish amplitudes.
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fn fixed_window() -> CsiWindow {
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let mut s = 0x00C0_FFEEu32;
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let data: Vec<f32> = (0..INPUT_SUBCARRIERS * INPUT_TIMESTEPS)
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.map(|_| {
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s = s.wrapping_mul(1103515245).wrapping_add(12345);
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(s >> 16) as f32 / 32768.0 // [0, 1)
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})
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.collect();
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CsiWindow { data }
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}
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/// Locate the real weights from the crate dir or the repo root.
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fn real_weights() -> Option<std::path::PathBuf> {
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let candidates = [
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"cog/artifacts/count_v1.safetensors",
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"v2/crates/cog-person-count/cog/artifacts/count_v1.safetensors",
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"crates/cog-person-count/cog/artifacts/count_v1.safetensors",
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];
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candidates
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.iter()
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.map(Path::new)
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.find(|p| p.exists())
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.map(|p| p.to_path_buf())
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}
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fn bench_infer(c: &mut Criterion) {
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let window = fixed_window();
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match real_weights() {
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Some(path) => {
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let engine =
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InferenceEngine::with_weights(Some(&path)).expect("load real count_v1 weights");
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assert!(
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engine.backend().starts_with("candle-"),
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"expected real Candle backend, got {} — bench would measure the stub",
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engine.backend()
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);
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// Sanity: one real inference before timing.
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let _ = engine.infer(&window).expect("warmup infer");
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c.bench_function("cog_person_count::infer[cpu_real_weights_steady_state]", |b| {
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b.iter(|| {
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black_box(engine.infer(black_box(&window)).expect("infer"));
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});
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});
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}
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None => {
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eprintln!(
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"NOTE: count_v1.safetensors not found — skipping the real-weights infer bench. \
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(The committed RESULTS.md numbers require the in-repo weights.)"
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);
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c.bench_function("cog_person_count::infer[SKIPPED_no_weights]", |b| {
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b.iter(|| black_box(1 + 1));
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});
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}
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}
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}
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criterion_group!(benches, bench_infer);
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criterion_main!(benches);
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@ -39,6 +39,12 @@ wifi-densepose-train = { version = "0.3.1", path = "../wifi-densepose-train", de
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[dev-dependencies]
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tempfile = "3"
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# ADR-163: steady-state infer latency bench (real pose_v1 weights, Device::Cpu).
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criterion = { version = "0.5", features = ["html_reports"] }
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[[bench]]
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name = "infer_bench"
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harness = false
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[features]
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default = []
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@ -0,0 +1,89 @@
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//! Criterion bench for `cog-pose-estimation` steady-state inference latency
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//! (ADR-163, closing the ADR-159/160 deferred "cog inference latency bench" item).
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//!
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//! ## What this measures — and what the manifest's `cold_start_ms_avg` does NOT
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//!
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//! The pose cog's manifest (`cog/artifacts/manifests/x86_64/manifest.json`)
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//! cites `build_metadata.cold_start_ms_avg: 5.4` (30 invocations, measured on
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//! ruvultra / RTX 5080 host, candle 0.9 cpu). **That is a cold-start number** —
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//! it folds in one-time weight load / mmap / first-forward allocation.
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//!
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//! This bench measures the **steady-state** per-frame cost instead:
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//! `InferenceEngine::infer` over a FIXED CSI window on `Device::Cpu` with the
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//! **real** shipped `pose_v1.safetensors`, after a warm-up forward. Steady-state
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//! and cold-start are different measurements; we label both honestly and do not
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//! claim this reproduces the 5.4 ms manifest figure (different machine, different
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//! measurement). See `benchmarks/edge-latency/RESULTS.md`.
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//!
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//! Run (cog crates are normal workspace members):
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//! cd v2 && cargo bench -p cog-pose-estimation --no-default-features
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//! cd v2 && cargo bench -p cog-pose-estimation --no-default-features -- --warm-up-time 1 --measurement-time 2
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use std::hint::black_box;
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use std::path::Path;
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use criterion::{criterion_group, criterion_main, Criterion};
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use cog_pose_estimation::inference::{
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CsiWindow, InferenceEngine, INPUT_SUBCARRIERS, INPUT_TIMESTEPS,
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};
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/// Deterministic fixed CSI window (seed-stable LCG).
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fn fixed_window() -> CsiWindow {
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let mut s = 0x00C0_FFEEu32;
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let data: Vec<f32> = (0..INPUT_SUBCARRIERS * INPUT_TIMESTEPS)
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.map(|_| {
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s = s.wrapping_mul(1103515245).wrapping_add(12345);
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(s >> 16) as f32 / 32768.0 // [0, 1)
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})
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.collect();
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CsiWindow { data }
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}
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fn real_weights() -> Option<std::path::PathBuf> {
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let candidates = [
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"cog/artifacts/pose_v1.safetensors",
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"v2/crates/cog-pose-estimation/cog/artifacts/pose_v1.safetensors",
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"crates/cog-pose-estimation/cog/artifacts/pose_v1.safetensors",
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];
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candidates
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.iter()
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.map(Path::new)
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.find(|p| p.exists())
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.map(|p| p.to_path_buf())
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}
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fn bench_infer(c: &mut Criterion) {
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let window = fixed_window();
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match real_weights() {
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Some(path) => {
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let engine =
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InferenceEngine::with_weights(Some(&path)).expect("load real pose_v1 weights");
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assert!(
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engine.backend().starts_with("candle-"),
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"expected real Candle backend, got {} — bench would measure the stub",
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engine.backend()
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);
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let _ = engine.infer(&window).expect("warmup infer");
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c.bench_function("cog_pose_estimation::infer[cpu_real_weights_steady_state]", |b| {
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b.iter(|| {
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black_box(engine.infer(black_box(&window)).expect("infer"));
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});
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});
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}
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None => {
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eprintln!(
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"NOTE: pose_v1.safetensors not found — skipping the real-weights infer bench. \
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(The committed RESULTS.md numbers require the in-repo weights.)"
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);
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c.bench_function("cog_pose_estimation::infer[SKIPPED_no_weights]", |b| {
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b.iter(|| black_box(1 + 1));
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});
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}
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}
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}
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criterion_group!(benches, bench_infer);
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criterion_main!(benches);
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