b7fd69815e
At 8 workers the GPU sat at ~5% util / <5GB VRAM — the pipeline is I/O-bound (downloading + decoding images over HTTP), so the GPU starves until many workers overlap that I/O. Raise MAX_CONCURRENCY 8→32 and make the UI worker control a number input (reaching 32 by ±1 was tedious); the cap is reported via /status so the UI clamps to it. Also size the shared requests pool (pool_maxsize=64) — the default 10 would have throttled 32 workers + spammed "connection pool is full". Verified by running; watch GPU util/VRAM climb as you dial up. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa
157 lines
5.9 KiB
Python
157 lines
5.9 KiB
Python
"""The lease → fetch → detect+embed → submit loop, run by a pool of worker
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slots whose count is tunable live from the UI.
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Each slot is an independent loop (its own leases; the server's SKIP-LOCKED lease
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keeps them from colliding). More slots = more GPU load + throughput; the model is
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loaded once and shared, so slots add concurrent inference, not N× model VRAM.
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That's the dial the operator turns to trade desktop responsiveness for speed.
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Stop (or shrinking the pool) RELEASES a slot's still-leased jobs immediately so
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orphaned work is re-picked at once rather than waiting out the lease.
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"""
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import threading
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import time
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from . import media, models
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from .client import FcClient
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from .config import Config
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from .crops import crop_region
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# Generous cap: the pipeline is usually I/O-bound (downloading + decoding images
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# over HTTP), so the GPU stays underused until many workers overlap that I/O.
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# Push it up while watching the GPU util + VRAM in the UI.
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MAX_CONCURRENCY = 32
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class _Slot:
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"""One worker loop. `inflight` = jobs leased but not yet processed, so a
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graceful stop can hand them back."""
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__slots__ = ("stop", "inflight")
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def __init__(self):
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self.stop = threading.Event()
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self.inflight: list[int] = []
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class Worker:
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def __init__(self, cfg: Config):
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self.cfg = cfg
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self.client = FcClient(cfg.fc_url, cfg.token, cfg.agent_id)
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self._lock = threading.Lock()
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self._running = False
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self._target = max(1, min(MAX_CONCURRENCY, cfg.concurrency))
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self._slots: list[_Slot] = []
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self.processed = 0
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self.errors = 0
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self._active = 0 # slots currently mid-image
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# --- control -----------------------------------------------------------
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def start(self):
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with self._lock:
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self._running = True
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self._reconcile_locked()
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def stop(self):
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with self._lock:
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self._running = False
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slots, self._slots = self._slots, []
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for s in slots:
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s.stop.set() # each slot releases its inflight on exit
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def set_concurrency(self, n: int):
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with self._lock:
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self._target = max(1, min(MAX_CONCURRENCY, int(n)))
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if self._running:
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self._reconcile_locked()
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def _reconcile_locked(self):
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while len(self._slots) < self._target:
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slot = _Slot()
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self._slots.append(slot)
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threading.Thread(target=self._loop, args=(slot,), daemon=True).start()
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while len(self._slots) > self._target:
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self._slots.pop().stop.set()
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def status(self) -> dict:
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with self._lock:
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return {
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"state": "running" if self._running else "stopped",
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"concurrency": self._target,
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"max_concurrency": MAX_CONCURRENCY,
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"workers": len(self._slots),
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"active": self._active,
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"processed": self.processed,
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"errors": self.errors,
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}
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def _bump(self, *, processed=0, errors=0, active=0):
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with self._lock:
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self.processed += processed
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self.errors += errors
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self._active += active
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# --- per-slot loop -----------------------------------------------------
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def _loop(self, slot: _Slot):
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while not slot.stop.is_set() and self._running:
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try:
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jobs = self.client.lease(self.cfg.batch_size)
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except Exception:
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time.sleep(self.cfg.poll_idle_seconds)
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continue
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if not jobs:
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time.sleep(self.cfg.poll_idle_seconds)
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continue
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slot.inflight = [j["job_id"] for j in jobs]
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for job in jobs:
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if slot.stop.is_set() or not self._running:
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break
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self._process(job)
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slot.inflight = [i for i in slot.inflight if i != job["job_id"]]
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if slot.inflight:
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self.client.heartbeat(slot.inflight)
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# Graceful hand-back of anything leased but not processed.
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if slot.inflight:
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self.client.release(slot.inflight)
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slot.inflight = []
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def _process(self, job: dict):
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self._bump(active=1)
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try:
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data = self.client.fetch_image(job["image_url"])
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if media.is_video(job.get("mime", "")):
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frames = media.sample_frames(
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data, job.get("frame_interval_seconds", 4.0),
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job.get("max_frames", 64),
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) or [(None, media.load_image(data))]
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else:
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frames = [(None, media.load_image(data))]
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regions = []
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ev = self.cfg.ccip_model or "ccip-default"
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dv = f"person-{self.cfg.detector_level}"
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for t, frame in frames:
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figs = models.detect_figures(frame, self.cfg.detector_level)
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if not figs:
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figs = [((0.0, 0.0, 1.0, 1.0), None)] # whole-frame fallback
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for bbox, score in figs:
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crop = crop_region(frame, bbox)
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if crop is None:
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continue
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vec = models.ccip_vector(crop, self.cfg.ccip_model or None)
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regions.append({
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"kind": "figure",
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"bbox": list(bbox),
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"frame_time": t,
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"score": score,
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"ccip_embedding": vec,
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"embedding_version": ev,
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"detector_version": dv,
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})
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self.client.submit(job["job_id"], regions, ["figure", "face"])
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self._bump(processed=1)
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except Exception as exc: # noqa: BLE001 — report + move on
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self._bump(errors=1)
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self.client.fail(job["job_id"], str(exc)[:500])
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finally:
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self._bump(active=-1)
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