365 lines
14 KiB
Python
365 lines
14 KiB
Python
|
from __future__ import annotations
|
||
|
|
|
||
|
|
import argparse
|
||
|
|
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||
|
|
from dataclasses import dataclass
|
||
|
|
from pathlib import Path
|
||
|
|
from typing import Any, Callable, Iterable
|
||
|
|
|
||
|
|
from candidate_preflight import CandidatePreflightAdvisor, MODEL_LOAD_OVERHEAD
|
||
|
|
from common import write_json
|
||
|
|
from hf_discovery import HuggingFaceDiscovery, inspect_repo_tree
|
||
|
|
from modelhub_client import ModelHubClient, ModelHubClientPool
|
||
|
|
from runner_common import DEFAULT_KEY_PATH, ensure_tokens
|
||
|
|
|
||
|
|
|
||
|
|
ACTIVE_FILTER_STATUSES = ("waiting", "running")
|
||
|
|
DEFAULT_STOP_BATCH_SIZE = 50
|
||
|
|
|
||
|
|
|
||
|
|
@dataclass(frozen=True)
|
||
|
|
class OwnedTask:
|
||
|
|
account_index: int
|
||
|
|
task_id: int
|
||
|
|
model_id: str
|
||
|
|
gpu_type: str
|
||
|
|
status: str
|
||
|
|
|
||
|
|
|
||
|
|
def _normalize_status(value: Any) -> str:
|
||
|
|
return str(value or "").strip().lower()
|
||
|
|
|
||
|
|
|
||
|
|
def _parse_owned_task(account_index: int, record: dict[str, Any]) -> OwnedTask | None:
|
||
|
|
task_id = record.get("taskId")
|
||
|
|
model_id = str(record.get("modelId") or "").strip()
|
||
|
|
gpu_type = str(record.get("gpuType") or "").strip()
|
||
|
|
status = _normalize_status(record.get("status"))
|
||
|
|
if not model_id or not gpu_type or status not in ACTIVE_FILTER_STATUSES:
|
||
|
|
return None
|
||
|
|
try:
|
||
|
|
numeric_task_id = int(str(task_id).strip())
|
||
|
|
except (TypeError, ValueError):
|
||
|
|
return None
|
||
|
|
if numeric_task_id <= 0:
|
||
|
|
return None
|
||
|
|
return OwnedTask(
|
||
|
|
account_index=account_index,
|
||
|
|
task_id=numeric_task_id,
|
||
|
|
model_id=model_id,
|
||
|
|
gpu_type=gpu_type,
|
||
|
|
status=status,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def _fetch_status_tasks(
|
||
|
|
client: ModelHubClient,
|
||
|
|
*,
|
||
|
|
account_index: int,
|
||
|
|
status: str,
|
||
|
|
page_size: int = 100,
|
||
|
|
) -> list[OwnedTask]:
|
||
|
|
current = 1
|
||
|
|
results: list[OwnedTask] = []
|
||
|
|
while True:
|
||
|
|
payload = client.list_tasks_page(
|
||
|
|
current=current,
|
||
|
|
page_size=page_size,
|
||
|
|
only_mine=True,
|
||
|
|
status=status,
|
||
|
|
)
|
||
|
|
page = payload.get("data") or {}
|
||
|
|
records = page.get("records") or []
|
||
|
|
if not isinstance(records, list):
|
||
|
|
raise ValueError("ModelHub task page records are invalid")
|
||
|
|
for record in records:
|
||
|
|
if not isinstance(record, dict):
|
||
|
|
continue
|
||
|
|
task = _parse_owned_task(account_index, record)
|
||
|
|
# The platform has silently ignored unknown status filters before.
|
||
|
|
# Accept only records whose returned state is explicitly active.
|
||
|
|
if task is not None:
|
||
|
|
results.append(task)
|
||
|
|
pages = int(page.get("pages") or 0)
|
||
|
|
if not records or current >= pages:
|
||
|
|
break
|
||
|
|
current += 1
|
||
|
|
return results
|
||
|
|
|
||
|
|
|
||
|
|
def collect_active_tasks(
|
||
|
|
clients: list[ModelHubClient],
|
||
|
|
*,
|
||
|
|
read_concurrency: int = 6,
|
||
|
|
statuses: Iterable[str] = ACTIVE_FILTER_STATUSES,
|
||
|
|
) -> tuple[list[OwnedTask], dict[int, list[str]]]:
|
||
|
|
"""Fetch active tasks from every account without sharing account-scoped reads."""
|
||
|
|
requested_statuses = tuple(dict.fromkeys(_normalize_status(status) for status in statuses))
|
||
|
|
tasks: list[OwnedTask] = []
|
||
|
|
errors: dict[int, list[str]] = {}
|
||
|
|
jobs = [(index, client, status) for index, client in enumerate(clients) for status in requested_statuses]
|
||
|
|
workers = min(max(1, int(read_concurrency)), max(1, len(jobs)))
|
||
|
|
with ThreadPoolExecutor(max_workers=workers) as executor:
|
||
|
|
futures = {
|
||
|
|
executor.submit(
|
||
|
|
_fetch_status_tasks,
|
||
|
|
client,
|
||
|
|
account_index=index,
|
||
|
|
status=status,
|
||
|
|
): (index, status)
|
||
|
|
for index, client, status in jobs
|
||
|
|
}
|
||
|
|
for future in as_completed(futures):
|
||
|
|
index, status = futures[future]
|
||
|
|
try:
|
||
|
|
tasks.extend(future.result())
|
||
|
|
except Exception as exc:
|
||
|
|
errors.setdefault(index, []).append(f"{status}: {type(exc).__name__}: {exc}")
|
||
|
|
|
||
|
|
deduped: dict[tuple[int, int], OwnedTask] = {}
|
||
|
|
for task in tasks:
|
||
|
|
deduped[(task.account_index, task.task_id)] = task
|
||
|
|
return sorted(deduped.values(), key=lambda item: (item.account_index, item.task_id)), errors
|
||
|
|
|
||
|
|
|
||
|
|
def _load_repository_sizes(
|
||
|
|
model_ids: set[str],
|
||
|
|
*,
|
||
|
|
discovery: HuggingFaceDiscovery,
|
||
|
|
read_concurrency: int,
|
||
|
|
log: Callable[[str], None],
|
||
|
|
) -> tuple[dict[str, int], dict[str, str]]:
|
||
|
|
sizes: dict[str, int] = {}
|
||
|
|
errors: dict[str, str] = {}
|
||
|
|
completed = 0
|
||
|
|
workers = min(max(1, int(read_concurrency)), max(1, len(model_ids)))
|
||
|
|
|
||
|
|
def inspect(model_id: str) -> tuple[str, int | None]:
|
||
|
|
tree = discovery.list_repo_tree(model_id)
|
||
|
|
return model_id, inspect_repo_tree(model_id, tree).repository_size_bytes
|
||
|
|
|
||
|
|
with ThreadPoolExecutor(max_workers=workers) as executor:
|
||
|
|
futures = {executor.submit(inspect, model_id): model_id for model_id in sorted(model_ids)}
|
||
|
|
for future in as_completed(futures):
|
||
|
|
model_id = futures[future]
|
||
|
|
try:
|
||
|
|
returned_model_id, size = future.result()
|
||
|
|
if size is None:
|
||
|
|
errors[returned_model_id] = "recursive_repository_size_incomplete"
|
||
|
|
else:
|
||
|
|
sizes[returned_model_id] = size
|
||
|
|
except Exception as exc:
|
||
|
|
errors[model_id] = f"{type(exc).__name__}: {exc}"
|
||
|
|
completed += 1
|
||
|
|
if completed == len(model_ids) or completed % 50 == 0:
|
||
|
|
log(
|
||
|
|
f"[queue-cleanup] size_scan={completed}/{len(model_ids)} "
|
||
|
|
f"complete={len(sizes)} unknown={len(errors)}"
|
||
|
|
)
|
||
|
|
return sizes, errors
|
||
|
|
|
||
|
|
|
||
|
|
def find_certain_oom_tasks(
|
||
|
|
tasks: list[OwnedTask],
|
||
|
|
*,
|
||
|
|
repository_sizes: dict[str, int],
|
||
|
|
gpu_memory_gib: dict[str, float] | None = None,
|
||
|
|
) -> tuple[list[dict[str, Any]], dict[str, int]]:
|
||
|
|
capacities = dict(CandidatePreflightAdvisor(gpu_memory_gib=gpu_memory_gib).gpu_memory_gib)
|
||
|
|
decisions: list[dict[str, Any]] = []
|
||
|
|
skipped = {
|
||
|
|
"repositorySizeUnknown": 0,
|
||
|
|
"gpuCapacityUnknown": 0,
|
||
|
|
"fitsKnownCapacity": 0,
|
||
|
|
}
|
||
|
|
for task in tasks:
|
||
|
|
size_bytes = repository_sizes.get(task.model_id)
|
||
|
|
if size_bytes is None:
|
||
|
|
skipped["repositorySizeUnknown"] += 1
|
||
|
|
continue
|
||
|
|
capacity_gib = capacities.get(task.gpu_type)
|
||
|
|
if capacity_gib is None:
|
||
|
|
skipped["gpuCapacityUnknown"] += 1
|
||
|
|
continue
|
||
|
|
repository_gib = size_bytes / (1024**3)
|
||
|
|
required_gib = repository_gib * MODEL_LOAD_OVERHEAD
|
||
|
|
if required_gib <= capacity_gib:
|
||
|
|
skipped["fitsKnownCapacity"] += 1
|
||
|
|
continue
|
||
|
|
decisions.append(
|
||
|
|
{
|
||
|
|
"accountIndex": task.account_index + 1,
|
||
|
|
"taskId": task.task_id,
|
||
|
|
"modelId": task.model_id,
|
||
|
|
"gpuType": task.gpu_type,
|
||
|
|
"status": task.status,
|
||
|
|
"repositorySizeGiB": round(repository_gib, 3),
|
||
|
|
"requiredGiB": round(required_gib, 3),
|
||
|
|
"gpuCapacityGiB": float(capacity_gib),
|
||
|
|
"reason": "certain_oom_repository_size_exceeds_gpu_capacity",
|
||
|
|
}
|
||
|
|
)
|
||
|
|
return decisions, skipped
|
||
|
|
|
||
|
|
|
||
|
|
def _chunks(values: list[int], size: int) -> Iterable[list[int]]:
|
||
|
|
for offset in range(0, len(values), size):
|
||
|
|
yield values[offset : offset + size]
|
||
|
|
|
||
|
|
|
||
|
|
def cleanup_certain_oom_tasks(
|
||
|
|
modelhub: ModelHubClientPool,
|
||
|
|
discovery: HuggingFaceDiscovery,
|
||
|
|
*,
|
||
|
|
dry_run: bool = False,
|
||
|
|
read_concurrency: int = 6,
|
||
|
|
stop_batch_size: int = DEFAULT_STOP_BATCH_SIZE,
|
||
|
|
gpu_memory_gib: dict[str, float] | None = None,
|
||
|
|
log: Callable[[str], None] = print,
|
||
|
|
) -> dict[str, Any]:
|
||
|
|
"""Stop only active tasks that cannot fit the selected GPU by known capacity."""
|
||
|
|
clients = list(modelhub.clients)
|
||
|
|
tasks, listing_errors = collect_active_tasks(clients, read_concurrency=read_concurrency)
|
||
|
|
log(
|
||
|
|
f"[queue-cleanup] active_scanned={len(tasks)} accounts={len(clients)} "
|
||
|
|
f"listing_errors={sum(len(items) for items in listing_errors.values())}"
|
||
|
|
)
|
||
|
|
|
||
|
|
model_ids = {task.model_id for task in tasks}
|
||
|
|
repository_sizes, size_errors = _load_repository_sizes(
|
||
|
|
model_ids,
|
||
|
|
discovery=discovery,
|
||
|
|
read_concurrency=read_concurrency,
|
||
|
|
log=log,
|
||
|
|
)
|
||
|
|
decisions, skipped = find_certain_oom_tasks(
|
||
|
|
tasks,
|
||
|
|
repository_sizes=repository_sizes,
|
||
|
|
gpu_memory_gib=gpu_memory_gib,
|
||
|
|
)
|
||
|
|
log(
|
||
|
|
f"[queue-cleanup] certain_oom={len(decisions)} "
|
||
|
|
f"fits={skipped['fitsKnownCapacity']} size_unknown={skipped['repositorySizeUnknown']} "
|
||
|
|
f"gpu_unknown={skipped['gpuCapacityUnknown']} dry_run={str(bool(dry_run)).lower()}"
|
||
|
|
)
|
||
|
|
|
||
|
|
cancelled: list[dict[str, Any]] = []
|
||
|
|
disappeared: list[dict[str, Any]] = []
|
||
|
|
stop_errors: list[dict[str, Any]] = []
|
||
|
|
if decisions and not dry_run:
|
||
|
|
# Re-read each account immediately before mutation. If any active-state
|
||
|
|
# query fails for that account, fail closed and do not terminate its tasks.
|
||
|
|
refreshed_tasks, refresh_errors = collect_active_tasks(clients, read_concurrency=read_concurrency)
|
||
|
|
active_ids_by_account: dict[int, set[int]] = {}
|
||
|
|
for task in refreshed_tasks:
|
||
|
|
active_ids_by_account.setdefault(task.account_index, set()).add(task.task_id)
|
||
|
|
|
||
|
|
for account_index, details in sorted(refresh_errors.items()):
|
||
|
|
stop_errors.append(
|
||
|
|
{
|
||
|
|
"accountIndex": account_index + 1,
|
||
|
|
"error": "active_task_recheck_failed",
|
||
|
|
"details": details,
|
||
|
|
}
|
||
|
|
)
|
||
|
|
|
||
|
|
by_account: dict[int, list[dict[str, Any]]] = {}
|
||
|
|
for decision in decisions:
|
||
|
|
account_index = int(decision["accountIndex"]) - 1
|
||
|
|
if account_index in refresh_errors:
|
||
|
|
continue
|
||
|
|
if int(decision["taskId"]) not in active_ids_by_account.get(account_index, set()):
|
||
|
|
disappeared.append(decision)
|
||
|
|
continue
|
||
|
|
by_account.setdefault(account_index, []).append(decision)
|
||
|
|
|
||
|
|
batch_size = max(1, min(100, int(stop_batch_size)))
|
||
|
|
stop_failed = False
|
||
|
|
for account_index in sorted(by_account):
|
||
|
|
if stop_failed:
|
||
|
|
break
|
||
|
|
decisions_by_id = {int(item["taskId"]): item for item in by_account[account_index]}
|
||
|
|
task_ids = sorted(decisions_by_id)
|
||
|
|
for batch in _chunks(task_ids, batch_size):
|
||
|
|
try:
|
||
|
|
clients[account_index].stop_tasks(batch)
|
||
|
|
except Exception as exc:
|
||
|
|
stop_errors.append(
|
||
|
|
{
|
||
|
|
"accountIndex": account_index + 1,
|
||
|
|
"taskIds": batch,
|
||
|
|
"error": f"{type(exc).__name__}: {exc}",
|
||
|
|
}
|
||
|
|
)
|
||
|
|
stop_failed = True
|
||
|
|
break
|
||
|
|
cancelled.extend(decisions_by_id[task_id] for task_id in batch)
|
||
|
|
log(
|
||
|
|
f"[queue-cleanup] account={account_index + 1:02d} "
|
||
|
|
f"cancelled_batch={len(batch)} cancelled_total={len(cancelled)}"
|
||
|
|
)
|
||
|
|
|
||
|
|
if cancelled and hasattr(modelhub, "refresh_active_counts"):
|
||
|
|
modelhub.refresh_active_counts()
|
||
|
|
|
||
|
|
return {
|
||
|
|
"dryRun": bool(dry_run),
|
||
|
|
"accounts": len(clients),
|
||
|
|
"activeScanned": len(tasks),
|
||
|
|
"uniqueModels": len(model_ids),
|
||
|
|
"repositorySizesComplete": len(repository_sizes),
|
||
|
|
"repositorySizeErrors": size_errors,
|
||
|
|
"listingErrors": {str(index + 1): values for index, values in listing_errors.items()},
|
||
|
|
"certainOomCount": len(decisions),
|
||
|
|
"certainOomTasks": decisions,
|
||
|
|
"skipped": skipped,
|
||
|
|
"cancelledCount": len(cancelled),
|
||
|
|
"cancelledTasks": cancelled,
|
||
|
|
"noLongerActiveCount": len(disappeared),
|
||
|
|
"stopErrors": stop_errors,
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
def build_parser() -> argparse.ArgumentParser:
|
||
|
|
parser = argparse.ArgumentParser(description="Safely stop active ModelHub tasks that are certain to run out of GPU memory.")
|
||
|
|
parser.add_argument("--execute", action="store_true", help="Actually terminate selected tasks; otherwise only print a preview")
|
||
|
|
parser.add_argument("--read-concurrency", type=int, default=6)
|
||
|
|
parser.add_argument("--stop-batch-size", type=int, default=DEFAULT_STOP_BATCH_SIZE)
|
||
|
|
parser.add_argument("--key-path", default=str(DEFAULT_KEY_PATH))
|
||
|
|
parser.add_argument("--modelhub-base-url", default="https://modelhub.org.cn")
|
||
|
|
parser.add_argument("--hf-base-url", default="https://modelscope.cn")
|
||
|
|
parser.add_argument("--modelhub-token", default=None)
|
||
|
|
parser.add_argument("--hf-token", default=None)
|
||
|
|
parser.add_argument("--modelscope-token", default=None)
|
||
|
|
parser.add_argument("--report-path", default=".modelhub_state/queue_cleanup_latest.json")
|
||
|
|
return parser
|
||
|
|
|
||
|
|
|
||
|
|
def main(argv: list[str] | None = None) -> int:
|
||
|
|
args = build_parser().parse_args(argv)
|
||
|
|
ensure_tokens(args)
|
||
|
|
tokens = list(getattr(args, "modelhub_tokens", None) or [args.modelhub_token])
|
||
|
|
clients = [ModelHubClient(token=token, base_url=args.modelhub_base_url) for token in tokens]
|
||
|
|
pool = ModelHubClientPool(clients, capacity_state_path=None)
|
||
|
|
discovery = HuggingFaceDiscovery(base_url=args.hf_base_url)
|
||
|
|
summary = cleanup_certain_oom_tasks(
|
||
|
|
pool,
|
||
|
|
discovery,
|
||
|
|
dry_run=not args.execute,
|
||
|
|
read_concurrency=args.read_concurrency,
|
||
|
|
stop_batch_size=args.stop_batch_size,
|
||
|
|
)
|
||
|
|
report_path = Path(args.report_path)
|
||
|
|
write_json(report_path, summary)
|
||
|
|
print(
|
||
|
|
f"[queue-cleanup] finished certain_oom={summary['certainOomCount']} "
|
||
|
|
f"cancelled={summary['cancelledCount']} stop_errors={len(summary['stopErrors'])} "
|
||
|
|
f"report={report_path}",
|
||
|
|
flush=True,
|
||
|
|
)
|
||
|
|
return 1 if summary["stopErrors"] else 0
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
raise SystemExit(main())
|