File size: 13,643 Bytes
eae424a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 | //! The inference worker: a thread that owns the meganeura session and
//! publishes coloured feature grids for the renderer to display.
//!
//! # Why a thread at all
//!
//! The encoder is expected to take 40–60 ms on a Quest 3 while the
//! compositor wants a frame every 13.9 ms. Running inference inline would
//! put the render loop on the encoder's cadence, which is uncomfortable at
//! best. Instead the renderer runs free, always drawing the most recent
//! completed result, and inference lands whenever it lands.
//!
//! # Why the worker builds its own session
//!
//! `meganeura::Session` is not `Send` — it owns a `CommandEncoder` holding
//! raw Vulkan handles. It cannot be constructed here and moved. What *is*
//! shareable is `Arc<blade_graphics::Context>`, so the worker receives the
//! context and builds the session in place. See `tests/threading.rs`.
//!
//! # The caveat this design cannot fix
//!
//! Both threads submit to the same Vulkan queue, which blade guards with a
//! mutex. A long compute submission can still delay the render submission
//! queued behind it — threading decouples *CPU* orchestration, not GPU
//! occupancy. Whether that shows up as dropped frames is exactly what the
//! on-device numbers will reveal; if it does, the fix is splitting the plan
//! across frames, which needs meganeura to grow partial execution
//! (`step()` currently submits every dispatch in one go).
use std::sync::atomic::{AtomicBool, AtomicU64, Ordering};
use std::sync::{Arc, Mutex, mpsc};
use std::time::Instant;
use crate::dinov3::Config;
use crate::pca::{self, Basis};
/// A completed inference result: a square RGB image, either the coarse
/// feature colouring or a full reconstruction.
#[derive(Debug, Clone)]
pub struct FeatureGrid {
/// Row-major RGB. For [`Display::PcaColour`] this is `[tokens, 3]`
/// including the prefix tokens; for [`Display::Reconstruction`] it is
/// already `[grid * grid, 3]` with no prefix.
pub colors: Vec<f32>,
/// Side length of the displayable square: the patch grid for PCA
/// colouring, the image size for a reconstruction.
pub grid: usize,
pub prefix_tokens: usize,
/// Encoder wall time, for the on-screen/logged rate readout.
pub latency_ms: f64,
}
impl FeatureGrid {
/// The displayable `grid × grid × 3` image, with any prefix tokens
/// dropped.
pub fn patch_rgb(&self) -> &[f32] {
&self.colors[self.prefix_tokens * pca::COMPONENTS..]
}
}
/// What the encoder's output is turned into for display.
#[derive(Clone, Debug)]
pub enum Display {
/// Project patch features onto their top three principal components and
/// read those off as RGB. No training, one `[hidden, 3]` matmul, and a
/// `grid × grid` result. Shows what the features *distinguish*.
PcaColour,
/// Reconstruct RGB through the trained decoder — the actual roundtrip.
/// Produces a full `image_size × image_size` picture, so the readback
/// per frame is ~600 KB rather than ~3 KB. Shows what the features
/// *retain*.
Reconstruction(std::path::PathBuf),
}
/// What the worker is told to do next.
enum Command {
/// Encode this image. `[num_patches, patch_dim]`, from
/// [`crate::preprocess`].
Submit(Vec<f32>),
/// Refit the PCA basis from the next frame's features.
Refit,
Stop,
}
/// Handle to a running worker.
pub struct Worker {
tx: mpsc::Sender<Command>,
latest: Arc<Mutex<Option<FeatureGrid>>>,
generation: Arc<AtomicU64>,
ready: Arc<AtomicBool>,
handle: Option<std::thread::JoinHandle<()>>,
}
impl Worker {
/// Queue a frame for encoding.
///
/// Returns `false` if the worker is busy or gone. Dropping frames is
/// the correct behaviour: the camera produces 60 Hz and the encoder
/// cannot keep up, so anything queued would be stale by the time it ran.
pub fn submit(&self, patches: Vec<f32>) -> bool {
if !self.ready.load(Ordering::Acquire) {
return false;
}
self.ready.store(false, Ordering::Release);
self.tx.send(Command::Submit(patches)).is_ok()
}
/// Ask for the colour basis to be refitted from the next frame.
pub fn request_refit(&self) {
let _ = self.tx.send(Command::Refit);
}
/// The most recent completed result, if any.
pub fn latest(&self) -> Option<FeatureGrid> {
self.latest.lock().ok().and_then(|g| g.clone())
}
/// Monotonic count of completed encodes, so the renderer can tell a
/// fresh result from a repeat without comparing pixel data.
pub fn generation(&self) -> u64 {
self.generation.load(Ordering::Acquire)
}
/// True when the worker is idle and would accept a frame.
pub fn is_ready(&self) -> bool {
self.ready.load(Ordering::Acquire)
}
}
impl Drop for Worker {
fn drop(&mut self) {
let _ = self.tx.send(Command::Stop);
if let Some(handle) = self.handle.take() {
let _ = handle.join();
}
}
}
/// How the worker should obtain its weights.
pub enum Weights {
/// Load a checkpoint from disk. On device this is a path the app has
/// pushed or unpacked from its assets.
SafeTensors(std::path::PathBuf),
/// Deterministic synthetic weights. Produces meaningless features, but
/// exercises the entire pipeline end to end — useful for bringing the
/// render path up before the real checkpoint is on the device.
Synthetic,
}
/// Start the worker.
///
/// Returns immediately; the session is built on the worker thread, which
/// takes a few seconds on a mobile CPU. [`Worker::is_ready`] reports false
/// until it is done, and [`Worker::latest`] yields `None`.
pub fn spawn(
gpu: Arc<blade_graphics::Context>,
config: Config,
weights: Weights,
plan_cache: Option<std::path::PathBuf>,
submission_chunks: usize,
display: Display,
) -> Worker {
let (tx, rx) = mpsc::channel();
let latest = Arc::new(Mutex::new(None));
let generation = Arc::new(AtomicU64::new(0));
let ready = Arc::new(AtomicBool::new(false));
let handle = {
let latest = Arc::clone(&latest);
let generation = Arc::clone(&generation);
let ready = Arc::clone(&ready);
std::thread::Builder::new()
.name("dinovision-inference".into())
.spawn(move || {
worker_main(
gpu,
config,
weights,
plan_cache,
submission_chunks,
display,
rx,
latest,
generation,
ready,
);
})
.expect("failed to spawn inference thread")
};
Worker {
tx,
latest,
generation,
ready,
handle: Some(handle),
}
}
#[allow(clippy::too_many_arguments)]
fn worker_main(
gpu: Arc<blade_graphics::Context>,
config: Config,
weights: Weights,
plan_cache: Option<std::path::PathBuf>,
submission_chunks: usize,
display: Display,
rx: mpsc::Receiver<Command>,
latest: Arc<Mutex<Option<FeatureGrid>>>,
generation: Arc<AtomicU64>,
ready: Arc<AtomicBool>,
) {
// For PCA colouring both the colours and the features are outputs:
// colours every frame (3 KB), features only when refitting the basis
// (300 KB), which is why they are separate. A reconstruction needs
// neither — the decoder consumes the features inside the graph.
let reconstructing = matches!(display, Display::Reconstruction(_));
let mut g = meganeura::Graph::new();
let features = crate::dinov3::build_encoder(&mut g, &config);
if reconstructing {
let rgb = crate::decoder::attach_to_encoder(&mut g, &config, features);
g.set_outputs(vec![rgb]);
} else {
let colors = pca::add_projection(&mut g, features, config.hidden_size);
g.set_outputs(vec![colors, features]);
}
let build_start = Instant::now();
let (mut session, _) = meganeura::train::build(&g, meganeura::train::SessionConfig {
mode: meganeura::train::Mode::Inference,
gpu: Some(gpu),
cache: plan_cache.as_deref(),
..Default::default()
});
log::info!(
"inference session ready in {:.1} s",
build_start.elapsed().as_secs_f64()
);
// Hand the queue back periodically so the renderer can get a frame in.
// One long submission is faster in isolation but starves everything
// else sharing the device.
session.set_submission_chunks(submission_chunks);
match weights {
Weights::SafeTensors(path) => {
match meganeura::data::safetensors::SafeTensorsModel::load(path.clone()) {
Ok(model) => {
if let Err(e) = crate::weights::load_encoder(&mut session, &model, &config) {
log::error!("failed to bind weights from {}: {e}", path.display());
return;
}
}
Err(e) => {
log::error!("failed to read {}: {e}", path.display());
return;
}
}
}
Weights::Synthetic => {
log::warn!("running with synthetic weights — features are meaningless");
crate::bench::fill_parameters(&mut session, &g);
}
}
let tokens = config.num_tokens();
let mut basis = Basis::placeholder(config.hidden_size);
let mut refit_pending = false;
let mut colors_out;
let mut features_out = vec![0.0f32; tokens * config.hidden_size];
// Reconstruction reads a planar [3, H, W] image; the renderer wants it
// interleaved, so keep a staging buffer for the transpose.
let mut planar = Vec::new();
match &display {
Display::PcaColour => {
// Start with a placeholder basis so the first frame displays
// something, then refit from real features as soon as one lands.
refit_pending = true;
apply_basis(&mut session, &basis);
colors_out = vec![0.0f32; tokens * pca::COMPONENTS];
}
Display::Reconstruction(path) => {
if let Err(e) = crate::decoder::load_parameters(&mut session, &g, path) {
log::error!("failed to load the decoder: {e}");
return;
}
let pixels = config.image_size * config.image_size;
planar = vec![0.0f32; 3 * pixels];
colors_out = vec![0.0f32; pixels * 3];
}
}
ready.store(true, Ordering::Release);
while let Ok(cmd) = rx.recv() {
let patches = match cmd {
Command::Submit(p) => p,
Command::Refit => {
refit_pending = true;
continue;
}
Command::Stop => break,
};
let start = Instant::now();
session.set_input("patches", &patches);
session.step();
session.wait();
if reconstructing {
session.read_output_by_index(0, &mut planar);
// [3, H, W] → [H * W, 3].
let pixels = config.image_size * config.image_size;
for p in 0..pixels {
for c in 0..3 {
colors_out[p * 3 + c] = planar[c * pixels + p];
}
}
} else {
session.read_output_by_index(0, &mut colors_out);
}
if refit_pending {
// Refitting needs the full feature matrix, so this frame pays
// for the larger readback. It happens once at startup and then
// only on request.
session.read_output_by_index(1, &mut features_out);
basis = Basis::fit(
&features_out,
tokens,
config.hidden_size,
config.num_prefix_tokens(),
);
apply_basis(&mut session, &basis);
refit_pending = false;
log::info!("refitted colour basis from live features");
// The colours just read were produced by the old basis; redo
// the projection on the CPU so this frame is not displayed with
// a stale palette.
colors_out = basis.project(&features_out, tokens);
}
let grid = FeatureGrid {
colors: colors_out.clone(),
grid: if reconstructing {
config.image_size
} else {
config.grid()
},
prefix_tokens: if reconstructing {
0
} else {
config.num_prefix_tokens()
},
latency_ms: start.elapsed().as_secs_f64() * 1000.0,
};
if let Ok(mut slot) = latest.lock() {
*slot = Some(grid);
}
generation.fetch_add(1, Ordering::Release);
ready.store(true, Ordering::Release);
}
log::info!("inference worker stopped");
}
fn apply_basis(session: &mut meganeura::Session, basis: &Basis) {
session.set_parameter("pca.weight", &basis.weight_matrix());
session.set_parameter("pca.bias", &basis.bias_vector());
}
|