feat: derive recent queue reserve from account capacity
This commit is contained in:
@@ -120,12 +120,12 @@ bash run_poll.sh --dry-run
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memory rule as new submissions. Only tasks whose own repository size times `1.20` exceeds
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their selected GPU capacity are stopped, after a fresh account-scoped active-state check.
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Incomplete size/capacity evidence is never used for cancellation.
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- Models older than seven days may occupy only positions 1–80 of each account's active queue.
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The account pool enforces the boundary atomically. Once all accounts reach 80, discovery no
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longer expands beyond seven days. Cleanup stops OOM tasks first, recalculates the surviving
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queue order, and on startup stops old tasks still ranked 81 or later. Scheduled cleanup then
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retains positions 81–95 and stops only old tasks ranked 96 or later. Recent overflow tasks stay.
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Unknown ModelScope timestamps never authorize a cancellation.
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- Models older than seven days may occupy only the current account capacity minus its final 10
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positions. The account pool enforces this per-account boundary atomically and updates it when
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capacity probing discovers a higher limit. Cleanup stops OOM tasks first, recalculates the
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surviving queue order, and applies the same limit-minus-10 boundary on startup. Scheduled
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cleanup relaxes to limit minus 5 to avoid excessive pruning. Recent overflow tasks stay, and
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unknown ModelScope timestamps never authorize a cancellation.
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## Important Flags
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@@ -161,10 +161,11 @@ Common flags:
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- `--max-cycles`: optional hard stop for testing or batch windows
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- `--disable-queue-cleanup`: disable automatic OOM and old-overflow queue cleanup
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The first automatic cleanup removes models older than seven days after each
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account's position 80. Later scheduled cleanups use position 95, while admission
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continues to reserve positions 81-100 for recent models. Override the later
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threshold with `MODELHUB_DYNAMIC_OLD_MODEL_CLEANUP_THRESHOLD`.
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The first automatic cleanup removes models older than seven days beyond each
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account's discovered capacity minus 10. Later scheduled cleanups use capacity
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minus 5, while admission continues to reserve the final 10 slots for recent
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models. Override these suffix sizes with `MODELHUB_RECENT_MODEL_RESERVE_SLOTS`
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and `MODELHUB_DYNAMIC_OLD_MODEL_CLEANUP_RESERVE_SLOTS`.
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Failure-informed preflight is enabled by default. It rejects deterministic
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missing-file and predicted-OOM cases, clamps unsafe context-length arguments,
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@@ -86,9 +86,9 @@ def build_parser() -> argparse.ArgumentParser:
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help="Maximum tasks to submit in one run (0 means unlimited)",
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)
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parser.add_argument(
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"--old-model-queue-threshold",
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"--recent-model-reserve-slots",
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type=int,
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default=int(os.getenv("MODELHUB_OLD_MODEL_QUEUE_THRESHOLD", "80")),
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default=int(os.getenv("MODELHUB_RECENT_MODEL_RESERVE_SLOTS", "10")),
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help=argparse.SUPPRESS,
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)
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parser.add_argument(
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@@ -252,7 +252,7 @@ def make_wave_namespace(base_args: argparse.Namespace, wave: WaveSpec) -> argpar
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capacity_probe_interval_cycles=getattr(base_args, "capacity_probe_interval_cycles", 3),
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submit_concurrency=getattr(base_args, "submit_concurrency", 1),
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max_submits_per_run=getattr(base_args, "max_submits_per_run", 0),
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old_model_queue_threshold=getattr(base_args, "old_model_queue_threshold", 80),
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recent_model_reserve_slots=getattr(base_args, "recent_model_reserve_slots", 10),
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recent_model_days=getattr(base_args, "recent_model_days", 7),
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disable_candidate_preflight=getattr(base_args, "disable_candidate_preflight", False),
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llm_classifier_endpoint=getattr(base_args, "llm_classifier_endpoint", None),
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@@ -109,9 +109,9 @@ def build_parser() -> argparse.ArgumentParser:
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help="Maximum tasks to submit in one run (0 means unlimited)",
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)
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parser.add_argument(
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"--old-model-queue-threshold",
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"--recent-model-reserve-slots",
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type=int,
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default=int(os.getenv("MODELHUB_OLD_MODEL_QUEUE_THRESHOLD", "80")),
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default=int(os.getenv("MODELHUB_RECENT_MODEL_RESERVE_SLOTS", "10")),
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help=argparse.SUPPRESS,
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)
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parser.add_argument(
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@@ -839,7 +839,7 @@ def run_submission(
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clients,
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capacity_probe_interval_cycles=max(0, int(getattr(args, "capacity_probe_interval_cycles", 3) or 0)),
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capacity_state_path=Path(getattr(args, "capacity_state_path", DEFAULT_CAPACITY_STATE_PATH)),
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old_model_queue_threshold=max(1, int(getattr(args, "old_model_queue_threshold", 80) or 80)),
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recent_model_reserve_slots=max(0, int(getattr(args, "recent_model_reserve_slots", 10) or 0)),
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recent_model_days=max(1, int(getattr(args, "recent_model_days", 7) or 7)),
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)
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@@ -1108,13 +1108,17 @@ def run_submission(
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pipeline_tags = pipeline_tags_for_task_types(selected_task_types)
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explicit_scan_cap = max(0, int(getattr(args, "max_scan_models", 0) or 0))
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recent_model_days = max(1, int(getattr(args, "recent_model_days", 7) or 7))
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old_model_queue_threshold = max(1, int(getattr(args, "old_model_queue_threshold", 80) or 80))
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recent_model_reserve_slots = max(0, int(getattr(args, "recent_model_reserve_slots", 10) or 0))
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old_model_slots_before_scan: int | None = None
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if hasattr(modelhub_client, "old_model_submit_slots"):
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old_model_slots_before_scan = int(modelhub_client.old_model_submit_slots())
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old_model_queue_thresholds: list[int] | None = None
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if hasattr(modelhub_client, "old_model_queue_thresholds"):
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old_model_queue_thresholds = list(modelhub_client.old_model_queue_thresholds())
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allow_older_models_for_scan = old_model_slots_before_scan is None or old_model_slots_before_scan > 0
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print(
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f"[age-policy] recent_days={recent_model_days} account_threshold={old_model_queue_threshold} "
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f"[age-policy] recent_days={recent_model_days} reserve_recent_slots={recent_model_reserve_slots} "
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f"account_thresholds={','.join(str(value) for value in old_model_queue_thresholds) if old_model_queue_thresholds is not None else 'n/a'} "
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f"old_model_slots={old_model_slots_before_scan if old_model_slots_before_scan is not None else 'n/a'} "
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f"scan_older={'on' if allow_older_models_for_scan else 'off'}",
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flush=True,
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@@ -1425,7 +1429,8 @@ def run_submission(
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"candidatePreflight": preflight_summary,
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"agePolicy": {
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"recentModelDays": recent_model_days,
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"oldModelSubmitThreshold": old_model_queue_threshold,
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"recentModelReserveSlots": recent_model_reserve_slots,
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"oldModelSubmitThresholds": old_model_queue_thresholds,
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"oldModelSlotsBeforeScan": old_model_slots_before_scan,
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"olderHistoryScanEnabled": allow_older_models_for_scan,
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},
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@@ -389,7 +389,7 @@ class ModelHubClientPool:
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capacity_probe_interval_cycles: int = 3,
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capacity_probe_cooldown_cycles: int = 3,
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capacity_state_path: Path | str | None = None,
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old_model_queue_threshold: int | None = None,
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recent_model_reserve_slots: int | None = None,
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recent_model_days: int | None = None,
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) -> None:
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if not clients:
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@@ -397,17 +397,17 @@ class ModelHubClientPool:
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self.clients = clients
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configured_cap = active_task_cap if active_task_cap is not None else os.getenv("MODELHUB_AGENT_ACTIVE_TASK_CAP", "100")
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self.active_task_cap = max(1, int(configured_cap))
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configured_old_threshold = (
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old_model_queue_threshold
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if old_model_queue_threshold is not None
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else os.getenv("MODELHUB_OLD_MODEL_QUEUE_THRESHOLD", "80")
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configured_recent_reserve = (
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recent_model_reserve_slots
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if recent_model_reserve_slots is not None
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else os.getenv("MODELHUB_RECENT_MODEL_RESERVE_SLOTS", "10")
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)
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configured_recent_days = (
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recent_model_days
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if recent_model_days is not None
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else os.getenv("MODELHUB_RECENT_MODEL_DAYS", "7")
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)
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self.old_model_queue_threshold = max(1, int(configured_old_threshold))
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self.recent_model_reserve_slots = max(0, int(configured_recent_reserve))
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self.recent_model_days = max(1, int(configured_recent_days))
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self._capacity_state_path = Path(capacity_state_path) if capacity_state_path else None
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self._account_keys = [self._account_key(client, index) for index, client in enumerate(clients)]
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@@ -491,6 +491,22 @@ class ModelHubClientPool:
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with self._state_lock:
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return list(self._account_caps)
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def observe_capacity_lower_bounds(self, active_counts: list[int | None]) -> list[int]:
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"""Promote known caps from complete account listings without guessing an upper bound."""
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caps_changed = False
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with self._state_lock:
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for index, value in enumerate(active_counts[: len(self._account_caps)]):
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if value is None:
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continue
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observed_count = max(0, int(value))
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if observed_count > self._account_caps[index]:
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self._account_caps[index] = observed_count
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caps_changed = True
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result = list(self._account_caps)
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if caps_changed:
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self._persist_account_caps()
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return result
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def capacity_probe_enabled(self) -> bool:
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with self._state_lock:
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return self._capacity_probe_enabled
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@@ -693,7 +709,7 @@ class ModelHubClientPool:
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self,
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excluded: set[int],
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*,
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effective_count_below: int | None = None,
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reserve_capacity_slots: int | None = None,
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) -> tuple[int, int] | None:
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with self._state_lock:
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remaining_by_index = {
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@@ -701,8 +717,9 @@ class ModelHubClientPool:
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for index in range(len(self.clients))
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if index not in excluded
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and (
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effective_count_below is None
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or self._effective_count_locked(index) < effective_count_below
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reserve_capacity_slots is None
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or self._effective_count_locked(index)
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< max(0, self._account_caps[index] - reserve_capacity_slots)
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)
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}
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usable = {index: remaining for index, remaining in remaining_by_index.items() if remaining > 0}
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@@ -727,7 +744,7 @@ class ModelHubClientPool:
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self,
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excluded: set[int],
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*,
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effective_count_below: int | None = None,
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reserve_capacity_slots: int | None = None,
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) -> tuple[int, int] | None:
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with self._state_lock:
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if not self._capacity_probe_enabled:
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@@ -740,8 +757,9 @@ class ModelHubClientPool:
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and self._capacity_probe_cycle >= self._capacity_probe_cooldown_until[index]
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and self._effective_count_locked(index) >= self._account_caps[index]
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and (
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effective_count_below is None
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or self._effective_count_locked(index) < effective_count_below
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reserve_capacity_slots is None
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or self._effective_count_locked(index)
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< max(0, self._account_caps[index] - reserve_capacity_slots)
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)
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]
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if not eligible:
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@@ -806,12 +824,19 @@ class ModelHubClientPool:
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return sum(
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max(
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0,
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min(self._account_caps[index], self.old_model_queue_threshold)
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- self._effective_count_locked(index),
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self._old_model_count_limit_locked(index) - self._effective_count_locked(index),
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)
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for index in range(len(self.clients))
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)
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def _old_model_count_limit_locked(self, index: int) -> int:
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return max(0, self._account_caps[index] - self.recent_model_reserve_slots)
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def old_model_queue_thresholds(self) -> list[int]:
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"""Return each account's current cap minus its recent-model reserve."""
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with self._state_lock:
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return [self._old_model_count_limit_locked(index) for index in range(len(self.clients))]
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def can_submit_old_models(self) -> bool:
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return self.old_model_submit_slots() > 0
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@@ -838,18 +863,18 @@ class ModelHubClientPool:
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attempted_accounts: set[int] = set()
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forced_refresh_done = False
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last_capacity_error: ModelHubAPIError | None = None
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account_count_limit = self.old_model_queue_threshold if old_model_only else None
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reserved_capacity_slots = self.recent_model_reserve_slots if old_model_only else None
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while True:
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reservation = self._reserve_account(
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attempted_accounts,
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effective_count_below=account_count_limit,
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reserve_capacity_slots=reserved_capacity_slots,
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)
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capacity_probe = False
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if reservation is None:
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reservation = self._reserve_probe_account(
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attempted_accounts,
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effective_count_below=account_count_limit,
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reserve_capacity_slots=reserved_capacity_slots,
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)
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capacity_probe = reservation is not None
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if reservation is None:
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@@ -860,8 +885,10 @@ class ModelHubClientPool:
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if last_capacity_error is not None:
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raise last_capacity_error
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if old_model_only:
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thresholds = self.old_model_queue_thresholds()
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raise OldModelQueuePolicyError(
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f"所有账号活动队列均已达到 {self.old_model_queue_threshold},"
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f"所有账号均已达到动态旧模型阈值 {thresholds}(账号上限减 "
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f"{self.recent_model_reserve_slots}),"
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f"仅允许提交最近 {self.recent_model_days} 天内更新的模型"
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)
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raise ModelHubAPIError(
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@@ -59,9 +59,9 @@ def build_parser() -> argparse.ArgumentParser:
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help="Maximum tasks to submit in one cycle (0 means unlimited)",
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)
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parser.add_argument(
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"--old-model-queue-threshold",
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"--recent-model-reserve-slots",
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type=int,
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default=int(os.getenv("MODELHUB_OLD_MODEL_QUEUE_THRESHOLD", "80")),
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default=int(os.getenv("MODELHUB_RECENT_MODEL_RESERVE_SLOTS", "10")),
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help=argparse.SUPPRESS,
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)
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parser.add_argument(
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@@ -71,9 +71,9 @@ def build_parser() -> argparse.ArgumentParser:
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help=argparse.SUPPRESS,
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)
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parser.add_argument(
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"--dynamic-old-model-cleanup-threshold",
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"--dynamic-old-model-cleanup-reserve-slots",
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type=int,
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default=int(os.getenv("MODELHUB_DYNAMIC_OLD_MODEL_CLEANUP_THRESHOLD", "95")),
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default=int(os.getenv("MODELHUB_DYNAMIC_OLD_MODEL_CLEANUP_RESERVE_SLOTS", "5")),
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help=argparse.SUPPRESS,
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)
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parser.add_argument("--disable-candidate-preflight", action="store_true", help=argparse.SUPPRESS)
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@@ -224,7 +224,7 @@ def _build_modelhub_client(base_args: argparse.Namespace) -> ModelHubClientPool:
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clients,
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capacity_probe_interval_cycles=max(0, int(getattr(base_args, "capacity_probe_interval_cycles", 3) or 0)),
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capacity_state_path=Path(getattr(base_args, "capacity_state_path", DEFAULT_CAPACITY_STATE_PATH)),
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old_model_queue_threshold=max(1, int(getattr(base_args, "old_model_queue_threshold", 80) or 80)),
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recent_model_reserve_slots=max(0, int(getattr(base_args, "recent_model_reserve_slots", 10) or 0)),
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recent_model_days=max(1, int(getattr(base_args, "recent_model_days", 7) or 7)),
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)
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@@ -234,18 +234,21 @@ def resolve_age_cleanup_policy(
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*,
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initial_cleanup_pending: bool,
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) -> tuple[str, int]:
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"""Use the strict admission boundary once, then retain a 15-slot buffer."""
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initial_threshold = max(
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1,
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int(getattr(base_args, "old_model_queue_threshold", 80) or 80),
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"""Reserve ten slots initially, then use a five-slot cleanup hysteresis."""
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initial_reserve_slots = max(
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0,
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int(getattr(base_args, "recent_model_reserve_slots", 10) or 0),
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)
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dynamic_threshold = max(
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initial_threshold,
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int(getattr(base_args, "dynamic_old_model_cleanup_threshold", 95) or 95),
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dynamic_reserve_slots = min(
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initial_reserve_slots,
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max(
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0,
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int(getattr(base_args, "dynamic_old_model_cleanup_reserve_slots", 5) or 0),
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),
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)
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if initial_cleanup_pending:
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return "initial", initial_threshold
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return "dynamic", dynamic_threshold
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return "initial", initial_reserve_slots
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return "dynamic", dynamic_reserve_slots
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def run_poll_loop(
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@@ -303,13 +306,13 @@ def run_poll_loop(
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try:
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cleanup_feedback = outcome_tracker.get_stats_report()
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cleanup_gpu_memory = cleanup_feedback.get("observedGpuMemoryGiB") or {}
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age_cleanup_mode, age_cleanup_threshold = resolve_age_cleanup_policy(
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age_cleanup_mode, age_cleanup_reserve_slots = resolve_age_cleanup_policy(
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base_args,
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initial_cleanup_pending=initial_age_cleanup_pending,
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)
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log(
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f"[queue-cleanup] mode={age_cleanup_mode} "
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f"old_model_threshold={age_cleanup_threshold} "
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f"reserve_recent_slots={age_cleanup_reserve_slots} "
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f"recent_days={max(1, int(getattr(base_args, 'recent_model_days', 7) or 7))}"
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)
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cleanup_summary = cleanup_certain_oom_tasks(
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@@ -318,7 +321,7 @@ def run_poll_loop(
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dry_run=bool(base_args.dry_run),
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read_concurrency=max(1, int(getattr(base_args, "queue_cleanup_read_concurrency", 6) or 6)),
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gpu_memory_gib=cleanup_gpu_memory if isinstance(cleanup_gpu_memory, dict) else None,
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age_queue_threshold=age_cleanup_threshold,
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age_reserved_slots=age_cleanup_reserve_slots,
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log=log,
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)
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write_json(
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@@ -335,7 +338,8 @@ def run_poll_loop(
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{
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"cycle": cycles,
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"mode": age_cleanup_mode,
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"ageQueueThreshold": age_cleanup_threshold,
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"ageReservedSlots": age_cleanup_reserve_slots,
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"ageQueueThresholds": cleanup_summary["oldModelQueueThresholds"],
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"activeScanned": cleanup_summary["activeScanned"],
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"certainOomCount": cleanup_summary["certainOomCount"],
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"oldOverflowCount": cleanup_summary["oldOverflowCount"],
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@@ -242,12 +242,11 @@ def find_old_overflow_tasks(
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tasks: list[OwnedTask],
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*,
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||||
model_last_modified: dict[str, datetime],
|
||||
queue_threshold: int = 80,
|
||||
queue_threshold: int | dict[int, int] = 80,
|
||||
recent_model_days: int = 7,
|
||||
reference_time: datetime | None = None,
|
||||
incomplete_accounts: set[int] | None = None,
|
||||
) -> tuple[list[dict[str, Any]], dict[str, int]]:
|
||||
threshold = max(1, int(queue_threshold))
|
||||
recent_days = max(1, int(recent_model_days))
|
||||
cutoff = (reference_time or utc_now()) - timedelta(days=recent_days)
|
||||
incomplete_accounts = incomplete_accounts or set()
|
||||
@@ -261,10 +260,19 @@ def find_old_overflow_tasks(
|
||||
"withinFirstQueuePositions": 0,
|
||||
"recentOverflowTasks": 0,
|
||||
"modelAgeUnknown": 0,
|
||||
"accountThresholdUnknown": 0,
|
||||
}
|
||||
for account_index, account_tasks in sorted(grouped.items()):
|
||||
if account_index in incomplete_accounts:
|
||||
continue
|
||||
if isinstance(queue_threshold, dict):
|
||||
configured_threshold = queue_threshold.get(account_index)
|
||||
if configured_threshold is None:
|
||||
skipped["accountThresholdUnknown"] += 1
|
||||
continue
|
||||
else:
|
||||
configured_threshold = queue_threshold
|
||||
threshold = max(0, int(configured_threshold))
|
||||
ordered = sorted(account_tasks, key=lambda item: item.task_id)
|
||||
skipped["withinFirstQueuePositions"] += min(threshold, len(ordered))
|
||||
for position, task in enumerate(ordered, start=1):
|
||||
@@ -307,19 +315,19 @@ def cleanup_certain_oom_tasks(
|
||||
read_concurrency: int = 6,
|
||||
stop_batch_size: int = DEFAULT_STOP_BATCH_SIZE,
|
||||
gpu_memory_gib: dict[str, float] | None = None,
|
||||
age_queue_threshold: int | None = None,
|
||||
age_reserved_slots: int | None = None,
|
||||
reference_time: datetime | None = None,
|
||||
log: Callable[[str], None] = print,
|
||||
) -> dict[str, Any]:
|
||||
"""Stop deterministic OOM tasks and old tasks beyond each account's protected prefix."""
|
||||
clients = list(modelhub.clients)
|
||||
reference_time = reference_time or utc_now()
|
||||
configured_queue_threshold = (
|
||||
age_queue_threshold
|
||||
if age_queue_threshold is not None
|
||||
else getattr(modelhub, "old_model_queue_threshold", 80)
|
||||
configured_reserved_slots = (
|
||||
age_reserved_slots
|
||||
if age_reserved_slots is not None
|
||||
else getattr(modelhub, "recent_model_reserve_slots", 10)
|
||||
)
|
||||
queue_threshold = max(1, int(configured_queue_threshold or 80))
|
||||
reserved_slots = max(0, int(configured_reserved_slots or 0))
|
||||
recent_model_days = max(1, int(getattr(modelhub, "recent_model_days", 7) or 7))
|
||||
tasks, listing_errors = collect_active_tasks(clients, read_concurrency=read_concurrency)
|
||||
log(
|
||||
@@ -327,6 +335,25 @@ def cleanup_certain_oom_tasks(
|
||||
f"listing_errors={sum(len(items) for items in listing_errors.values())}"
|
||||
)
|
||||
|
||||
observed_active_counts: list[int | None] = [0 for _ in clients]
|
||||
for task in tasks:
|
||||
current_count = observed_active_counts[task.account_index]
|
||||
if current_count is not None:
|
||||
observed_active_counts[task.account_index] = current_count + 1
|
||||
for account_index in listing_errors:
|
||||
observed_active_counts[account_index] = None
|
||||
if hasattr(modelhub, "observe_capacity_lower_bounds"):
|
||||
account_caps = list(modelhub.observe_capacity_lower_bounds(observed_active_counts))
|
||||
elif hasattr(modelhub, "account_capacity_limits"):
|
||||
account_caps = list(modelhub.account_capacity_limits())
|
||||
else:
|
||||
default_cap = max(1, int(getattr(modelhub, "active_task_cap", 100) or 100))
|
||||
account_caps = [default_cap for _ in clients]
|
||||
queue_thresholds = {
|
||||
index: max(0, int(account_caps[index]) - reserved_slots)
|
||||
for index in range(min(len(clients), len(account_caps)))
|
||||
}
|
||||
|
||||
model_ids = {task.model_id for task in tasks}
|
||||
repository_sizes, size_errors = _load_repository_sizes(
|
||||
model_ids,
|
||||
@@ -362,7 +389,7 @@ def cleanup_certain_oom_tasks(
|
||||
for task in sorted(
|
||||
(item for item in age_rank_tasks if item.account_index == account_index),
|
||||
key=lambda item: item.task_id,
|
||||
)[queue_threshold:]
|
||||
)[queue_thresholds.get(account_index, len(age_rank_tasks)):]
|
||||
}
|
||||
model_last_modified, age_errors = _load_model_last_modified(
|
||||
overflow_model_ids,
|
||||
@@ -373,14 +400,15 @@ def cleanup_certain_oom_tasks(
|
||||
old_overflow_decisions, age_skipped = find_old_overflow_tasks(
|
||||
age_rank_tasks,
|
||||
model_last_modified=model_last_modified,
|
||||
queue_threshold=queue_threshold,
|
||||
queue_threshold=queue_thresholds,
|
||||
recent_model_days=recent_model_days,
|
||||
reference_time=reference_time,
|
||||
incomplete_accounts=set(listing_errors),
|
||||
)
|
||||
log(
|
||||
f"[queue-cleanup] old_overflow={len(old_overflow_decisions)} "
|
||||
f"threshold={queue_threshold} recent_days={recent_model_days} "
|
||||
f"thresholds={','.join(str(queue_thresholds[index]) for index in sorted(queue_thresholds))} "
|
||||
f"reserve_recent_slots={reserved_slots} recent_days={recent_model_days} "
|
||||
f"recent_overflow={age_skipped['recentOverflowTasks']} "
|
||||
f"age_unknown={age_skipped['modelAgeUnknown']}"
|
||||
)
|
||||
@@ -453,7 +481,12 @@ def cleanup_certain_oom_tasks(
|
||||
cleanup_reasons = set(decision.get("cleanupReasons") or [decision.get("reason")])
|
||||
age_only = cleanup_reasons == {"old_model_beyond_account_queue_threshold"}
|
||||
current_position = active_positions_by_account.get(account_index, {}).get(int(decision["taskId"]))
|
||||
if age_only and (current_position is None or current_position <= queue_threshold):
|
||||
account_queue_threshold = queue_thresholds.get(account_index)
|
||||
if age_only and (
|
||||
current_position is None
|
||||
or account_queue_threshold is None
|
||||
or current_position <= account_queue_threshold
|
||||
):
|
||||
policy_no_longer_applies.append(
|
||||
{**decision, "recheckedQueuePosition": current_position}
|
||||
)
|
||||
@@ -516,7 +549,14 @@ def cleanup_certain_oom_tasks(
|
||||
"certainOomTasks": oom_decisions,
|
||||
"oldOverflowCount": len(old_overflow_decisions),
|
||||
"oldOverflowTasks": old_overflow_decisions,
|
||||
"oldModelQueueThreshold": queue_threshold,
|
||||
"oldModelQueueThresholds": [
|
||||
queue_thresholds.get(index) for index in range(len(clients))
|
||||
],
|
||||
"accountCapacityLimits": [
|
||||
account_caps[index] if index < len(account_caps) else None
|
||||
for index in range(len(clients))
|
||||
],
|
||||
"recentModelReserveSlots": reserved_slots,
|
||||
"recentModelDays": recent_model_days,
|
||||
"agePolicySkipped": age_skipped,
|
||||
"cleanupCandidateCount": len(decisions),
|
||||
|
||||
@@ -1 +1 @@
|
||||
AGENT_VERSION = "2026.08.11.3"
|
||||
AGENT_VERSION = "2026.08.11.4"
|
||||
|
||||
Reference in New Issue
Block a user