mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2026-10-18 14:43:29 +08:00
yyj
7c35863f62
* ci: add isolated model E2E acceptance for PR wheels and PyPI * ci: recheck GPU occupancy before each model starts * ci: disable inherited container healthchecks during acceptance * ci: wait for free GPUs before native import validation * docs: record qj5090 acceptance infrastructure validation * ci: add immutable candidate and public PyPI release acceptance gates
98 lines
3.2 KiB
Python
98 lines
3.2 KiB
Python
"""Wait without allocating GPU memory; hold one host-wide advisory lock."""
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from __future__ import annotations
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import contextlib
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import fcntl
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import json
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import subprocess
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import time
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from pathlib import Path
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class ResourceUnavailable(RuntimeError):
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pass
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def gpu_busy():
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"""Fail closed on driver/query failures, and include non-compute VRAM users."""
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apps = subprocess.check_output(
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["nvidia-smi", "--query-compute-apps=pid", "--format=csv,noheader,nounits"],
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text=True,
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timeout=20,
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).strip()
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stats = subprocess.check_output(
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[
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"nvidia-smi",
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"--query-gpu=memory.used,utilization.gpu",
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"--format=csv,noheader,nounits",
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],
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text=True,
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timeout=20,
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).strip()
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if not stats:
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raise ResourceUnavailable("No GPUs found")
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try:
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rows = [
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[int(value.strip()) for value in row.split(",")]
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for row in stats.splitlines()
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]
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busy = bool(apps) or any(
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memory > 256 or utilization > 5 for memory, utilization in rows
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)
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except (ValueError, TypeError) as exc:
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raise ResourceUnavailable("Cannot determine GPU usage") from exc
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return busy, {"compute_pids": apps, "gpu_memory_mib_utilization": rows}
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@contextlib.contextmanager
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def reservation(
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lock_path, log_path, timeout=21600, interval=15, idle_samples=3, probe=gpu_busy
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):
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"""No Actions concurrency group: it can replace older pending jobs.
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A persistent lock inode must never be deleted after use. Manual workloads
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should acquire the same lock to close the idle-check/start race.
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"""
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lock_path = Path(lock_path)
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if not lock_path.parent.is_dir():
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raise ResourceUnavailable(
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"Administrator must provision the shared lock directory"
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)
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deadline = time.monotonic() + timeout
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stable = 0
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with lock_path.open("a") as lock, Path(log_path).open("a") as log:
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owned = False
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try:
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while time.monotonic() < deadline:
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if not owned:
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try:
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fcntl.flock(lock, fcntl.LOCK_EX | fcntl.LOCK_NB)
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owned = True
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except BlockingIOError:
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pass
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state = {
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"status": "waiting_for_qj5090",
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"reason": "another CI reservation",
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}
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if owned:
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busy, evidence = probe()
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stable = 0 if busy else stable + 1
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state.update(evidence)
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state["reason"] = (
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"GPU workload present" if busy else "checking stable idle"
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)
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if stable >= idle_samples:
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log.write(json.dumps({"status": "reserved"}) + "\n")
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log.flush()
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yield
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return
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print(json.dumps(state), flush=True)
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log.write(json.dumps(state) + "\n")
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log.flush()
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time.sleep(interval)
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raise ResourceUnavailable("Queue wait expired; no model test was run")
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finally:
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if owned:
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fcntl.flock(lock, fcntl.LOCK_UN)
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