Files
submmit/tests/test_queue_cleanup.py

643 lines
24 KiB
Python

from __future__ import annotations
import unittest
import sys
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
PACKAGE_DIR = Path(__file__).resolve().parents[1] / "modelhub_submmit_api"
if str(PACKAGE_DIR) in sys.path:
sys.path.remove(str(PACKAGE_DIR))
sys.path.insert(0, str(PACKAGE_DIR))
from architecture_compatibility import architecture_compatibility_key # noqa: E402
from modelhub_client import ModelHubClient, ModelHubClientPool # noqa: E402
from queue_cleanup import ( # noqa: E402
OwnedTask,
cleanup_certain_oom_tasks,
find_architecture_incompatible_tasks,
find_certain_oom_tasks,
find_old_overflow_tasks,
)
GIB = 1024**3
class FakeQueueClient:
def __init__(
self,
records: list[dict[str, Any]],
*,
disappear_on_recheck: bool = False,
drop_first_on_recheck: bool = False,
promote_on_waiting_read: int | None = None,
) -> None:
self.records = list(records)
self.disappear_on_recheck = disappear_on_recheck
self.drop_first_on_recheck = drop_first_on_recheck
self.promote_on_waiting_read = promote_on_waiting_read
self.waiting_reads = 0
self.stopped: list[list[int]] = []
def list_tasks_page(self, *, status: str, **_kwargs: Any) -> dict[str, Any]:
if status == "waiting":
self.waiting_reads += 1
if self.promote_on_waiting_read == self.waiting_reads:
waiting = [record for record in self.records if record["status"] == "waiting"]
if waiting:
max(waiting, key=lambda item: int(item["taskId"]))["status"] = "running"
if self.disappear_on_recheck and self.waiting_reads >= 2:
records: list[dict[str, Any]] = []
else:
records = [record for record in self.records if record["status"] == "waiting"]
if self.drop_first_on_recheck and self.waiting_reads >= 2:
records = sorted(records, key=lambda item: int(item["taskId"]))[1:]
else:
records = [record for record in self.records if record["status"] == status]
return {"code": 0, "data": {"records": records, "pages": 1}}
def stop_tasks(self, task_ids: list[int]) -> dict[str, Any]:
self.stopped.append(list(task_ids))
ids = set(task_ids)
self.records = [record for record in self.records if int(record["taskId"]) not in ids]
return {"code": 0, "data": None}
def count_active_tasks(self, **_kwargs: Any) -> int:
return len(self.records)
class FakeDiscovery:
def __init__(
self,
sizes: dict[str, int | None],
last_modified: dict[str, datetime | None] | None = None,
configs: dict[str, dict[str, Any]] | None = None,
) -> None:
self.sizes = sizes
self.last_modified = last_modified or {}
self.configs = configs or {}
def list_repo_tree(self, repo_id: str) -> list[dict[str, Any]]:
size = self.sizes[repo_id]
if size is None:
return [{"Path": "model.safetensors"}]
return [{"Path": "model.safetensors", "Size": size}]
def get_model_last_modified(self, repo_id: str) -> datetime | None:
return self.last_modified.get(repo_id)
def get_model_config(self, repo_id: str) -> tuple[dict[str, Any], str | None]:
config = self.configs.get(repo_id)
return (dict(config), None) if config is not None else ({}, "config_not_found")
class RecordingHttpClient:
def __init__(self) -> None:
self.calls: list[tuple[str, str, dict[str, Any] | None, dict[str, Any] | None]] = []
def request_json(
self,
method: str,
path: str,
*,
query: dict[str, Any] | None = None,
data: dict[str, Any] | None = None,
) -> dict[str, Any]:
self.calls.append((method, path, query, data))
return {"code": 0, "data": None}
class QueueCleanupTests(unittest.TestCase):
@staticmethod
def architecture_block(
*,
gpu: str = "Iluvatar_bi-100",
framework: str = "vllm",
task_type: str = "text-generation",
signature: str = "architectures:qwen2forcausallm",
) -> tuple[str, dict[str, Any]]:
key = architecture_compatibility_key(gpu, framework, task_type, signature)
assert key is not None
return key, {
"targetGpu": gpu,
"framework": framework,
"taskType": task_type,
"matchType": "architectures",
"architectureSignature": signature,
"evidenceCount": 1,
"expiresAt": "2026-09-11T00:00:00+00:00",
}
def test_architecture_cleanup_matches_exact_context_and_protects_running(self) -> None:
key, block = self.architecture_block()
tasks = [
OwnedTask(0, 1, "owner/waiting", "Iluvatar_bi-100", "waiting"),
OwnedTask(0, 2, "owner/running", "Iluvatar_bi-100", "running"),
OwnedTask(0, 3, "owner/other-framework", "Iluvatar_bi-100", "waiting"),
]
contexts = {
"1": {
"modelId": "owner/waiting",
"targetGpu": "Iluvatar_bi-100",
"framework": "vllm",
"taskType": "text-generation",
"modelProfile": {"architectures": ["Qwen2ForCausalLM"]},
},
"2": {
"modelId": "owner/running",
"targetGpu": "Iluvatar_bi-100",
"framework": "vllm",
"taskType": "text-generation",
"modelProfile": {"architectures": ["Qwen2ForCausalLM"]},
},
"3": {
"modelId": "owner/other-framework",
"targetGpu": "Iluvatar_bi-100",
"framework": "mindie",
"taskType": "text-generation",
"modelProfile": {"architectures": ["Qwen2ForCausalLM"]},
},
}
selected, skipped = find_architecture_incompatible_tasks(
tasks,
architecture_blocks={key: block},
task_contexts=contexts,
model_configs={},
)
self.assertEqual([1], [item["taskId"] for item in selected])
self.assertEqual(1, skipped["runningMatchedProtected"])
self.assertEqual(1, skipped["noMatchingBlock"])
def test_queue_cleanup_fetches_config_and_stops_known_incompatible_waiting_task(self) -> None:
key, block = self.architecture_block()
client = FakeQueueClient(
[
{
"taskId": 1,
"modelId": "owner/model",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
]
)
pool = ModelHubClientPool([client], active_task_cap=100) # type: ignore[list-item]
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/model": 1 * GIB},
configs={
"owner/model": {
"model_type": "qwen2",
"architectures": ["Qwen2ForCausalLM"],
}
},
), # type: ignore[arg-type]
architecture_compatibility_blocks={key: block},
task_compatibility_contexts={
"1": {
"modelId": "owner/model",
"targetGpu": "Iluvatar_bi-100",
"framework": "vllm",
"taskType": "text-generation",
"modelProfile": {},
}
},
log=lambda _message: None,
)
self.assertEqual(1, summary["architectureIncompatibleCount"])
self.assertEqual(1, summary["cancelledCount"])
self.assertEqual([[1]], client.stopped)
def test_dynamic_architecture_only_cleanup_skips_expensive_size_and_age_scans(self) -> None:
key, block = self.architecture_block()
client = FakeQueueClient(
[
{
"taskId": 1,
"modelId": "owner/model",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
]
)
pool = ModelHubClientPool([client], active_task_cap=100) # type: ignore[list-item]
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery({}), # type: ignore[arg-type]
architecture_compatibility_blocks={key: block},
task_compatibility_contexts={
"1": {
"modelId": "owner/model",
"targetGpu": "Iluvatar_bi-100",
"framework": "vllm",
"taskType": "text-generation",
"modelProfile": {"architectures": ["Qwen2ForCausalLM"]},
}
},
architecture_only=True,
log=lambda _message: None,
)
self.assertTrue(summary["architectureOnly"])
self.assertEqual(0, summary["repositorySizesComplete"])
self.assertEqual(0, summary["modelAgeMetadataComplete"])
self.assertEqual(1, summary["architectureIncompatibleCount"])
self.assertEqual([[1]], client.stopped)
def test_architecture_cleanup_recheck_protects_task_that_started_running(self) -> None:
key, block = self.architecture_block()
client = FakeQueueClient(
[
{
"taskId": 1,
"modelId": "owner/model",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
],
promote_on_waiting_read=2,
)
pool = ModelHubClientPool([client], active_task_cap=100) # type: ignore[list-item]
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery({"owner/model": 1 * GIB}), # type: ignore[arg-type]
architecture_compatibility_blocks={key: block},
task_compatibility_contexts={
"1": {
"modelId": "owner/model",
"targetGpu": "Iluvatar_bi-100",
"framework": "vllm",
"taskType": "text-generation",
"modelProfile": {"architectures": ["Qwen2ForCausalLM"]},
}
},
read_concurrency=1,
log=lambda _message: None,
)
self.assertEqual(1, summary["architectureIncompatibleCount"])
self.assertEqual(0, summary["cancelledCount"])
self.assertEqual("task_started_running", summary["policyNoLongerAppliesTasks"][0]["policyChangeReason"])
self.assertEqual([], client.stopped)
def test_old_models_use_each_accounts_own_capacity_minus_ten_threshold(self) -> None:
now = datetime(2026, 8, 11, tzinfo=timezone.utc)
tasks = [
OwnedTask(0, index, "owner/old", "Iluvatar_bi-100", "waiting")
for index in range(1, 92)
]
tasks.extend(
OwnedTask(1, 1000 + index, "owner/old", "Iluvatar_bi-100", "waiting")
for index in range(1, 192)
)
tasks.append(OwnedTask(0, 92, "owner/recent", "Iluvatar_bi-100", "waiting"))
tasks.append(OwnedTask(0, 93, "owner/old", "Iluvatar_bi-100", "running"))
tasks.append(OwnedTask(1, 1192, "owner/recent", "Iluvatar_bi-100", "waiting"))
selected, skipped = find_old_overflow_tasks(
tasks,
model_last_modified={
"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc),
"owner/recent": datetime(2026, 8, 10, tzinfo=timezone.utc),
},
queue_threshold={0: 90, 1: 190},
recent_model_days=7,
reference_time=now,
)
self.assertEqual([91, 1191], [item["taskId"] for item in selected])
self.assertEqual([91, 191], [item["queuePosition"] for item in selected])
self.assertEqual(2, skipped["recentOverflowTasks"])
self.assertEqual(1, skipped["runningOverflowProtected"])
def test_age_cleanup_never_stops_running_overflow_task(self) -> None:
records = [
{
"taskId": index,
"modelId": "owner/old",
"gpuType": "Iluvatar_bi-100",
"status": "running" if index == 91 else "waiting",
}
for index in range(1, 92)
]
client = FakeQueueClient(records)
pool = ModelHubClientPool(
[client], # type: ignore[list-item]
active_task_cap=100,
recent_model_reserve_slots=10,
)
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/old": 1 * GIB},
{"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc)},
), # type: ignore[arg-type]
reference_time=datetime(2026, 8, 11, tzinfo=timezone.utc),
log=lambda _message: None,
)
self.assertEqual(0, summary["oldOverflowCount"])
self.assertEqual(1, summary["agePolicySkipped"]["runningOverflowProtected"])
self.assertEqual([], client.stopped)
def test_age_cleanup_recheck_releases_task_that_started_running(self) -> None:
records = [
{
"taskId": index,
"modelId": "owner/old",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
for index in range(1, 92)
]
# Read 1 is discovery, read 2 is the account-wide mutation recheck,
# and read 3 is the final age-only recheck after the OOM phase.
client = FakeQueueClient(records, promote_on_waiting_read=3)
pool = ModelHubClientPool(
[client], # type: ignore[list-item]
active_task_cap=100,
recent_model_reserve_slots=10,
)
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/old": 1 * GIB},
{"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc)},
), # type: ignore[arg-type]
read_concurrency=1,
reference_time=datetime(2026, 8, 11, tzinfo=timezone.utc),
log=lambda _message: None,
)
self.assertEqual(1, summary["oldOverflowCount"])
self.assertEqual(0, summary["cancelledCount"])
self.assertEqual("task_started_running", summary["policyNoLongerAppliesTasks"][0]["policyChangeReason"])
self.assertEqual([], client.stopped)
def test_certain_oom_cleanup_can_still_stop_running_task(self) -> None:
client = FakeQueueClient(
[
{
"taskId": 1,
"modelId": "owner/large",
"gpuType": "Iluvatar_bi-100",
"status": "running",
}
]
)
pool = ModelHubClientPool([client], active_task_cap=100) # type: ignore[list-item]
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery({"owner/large": 40 * GIB}), # type: ignore[arg-type]
log=lambda _message: None,
)
self.assertEqual(1, summary["certainOomCount"])
self.assertEqual(1, summary["cancelledCount"])
self.assertEqual([[1]], client.stopped)
def test_old_overflow_task_is_not_stopped_if_it_moves_inside_dynamic_threshold(self) -> None:
records = [
{
"taskId": index,
"modelId": "owner/old",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
for index in range(1, 92)
]
client = FakeQueueClient(records, drop_first_on_recheck=True)
pool = ModelHubClientPool(
[client], # type: ignore[list-item]
active_task_cap=100,
recent_model_reserve_slots=10,
)
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/old": 1 * GIB},
{"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc)},
), # type: ignore[arg-type]
reference_time=datetime(2026, 8, 11, tzinfo=timezone.utc),
log=lambda _message: None,
)
self.assertEqual(1, summary["oldOverflowCount"])
self.assertEqual(0, summary["cancelledCount"])
self.assertEqual(1, summary["policyNoLongerAppliesCount"])
self.assertEqual([], client.stopped)
def test_cleanup_promotes_capacity_from_complete_active_listing(self) -> None:
records = [
{
"taskId": index,
"modelId": "owner/old",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
for index in range(1, 151)
]
client = FakeQueueClient(records)
pool = ModelHubClientPool(
[client], # type: ignore[list-item]
active_task_cap=100,
recent_model_reserve_slots=10,
capacity_state_path=None,
)
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/old": 1 * GIB},
{"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc)},
), # type: ignore[arg-type]
reference_time=datetime(2026, 8, 11, tzinfo=timezone.utc),
log=lambda _message: None,
)
self.assertEqual([150], summary["accountCapacityLimits"])
self.assertEqual([140], summary["oldModelQueueThresholds"])
self.assertEqual(list(range(141, 151)), [item["taskId"] for item in summary["oldOverflowTasks"]])
def test_initial_cleanup_stops_old_task_beyond_capacity_minus_ten(self) -> None:
records = [
{
"taskId": index,
"modelId": "owner/old",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
for index in range(1, 92)
]
client = FakeQueueClient(records)
pool = ModelHubClientPool(
[client], # type: ignore[list-item]
active_task_cap=100,
recent_model_reserve_slots=10,
)
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/old": 1 * GIB},
{"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc)},
), # type: ignore[arg-type]
reference_time=datetime(2026, 8, 11, tzinfo=timezone.utc),
log=lambda _message: None,
)
self.assertEqual(1, summary["oldOverflowCount"])
self.assertEqual(1, summary["cancelledCount"])
self.assertEqual([90], summary["oldModelQueueThresholds"])
self.assertEqual([[91]], client.stopped)
def test_scheduled_cleanup_uses_capacity_minus_five(self) -> None:
records = [
{
"taskId": index,
"modelId": "owner/old",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
for index in range(1, 97)
]
client = FakeQueueClient(records)
pool = ModelHubClientPool(
[client], # type: ignore[list-item]
active_task_cap=100,
recent_model_reserve_slots=10,
)
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/old": 1 * GIB},
{"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc)},
), # type: ignore[arg-type]
age_reserved_slots=5,
reference_time=datetime(2026, 8, 11, tzinfo=timezone.utc),
log=lambda _message: None,
)
self.assertEqual([95], summary["oldModelQueueThresholds"])
self.assertEqual([96], [item["taskId"] for item in summary["oldOverflowTasks"]])
self.assertEqual([[96]], client.stopped)
def test_oom_is_removed_before_recalculating_old_overflow_positions(self) -> None:
records = [
{
"taskId": index,
"modelId": "owner/large" if index == 1 else "owner/old",
"gpuType": "Iluvatar_bi-100",
"status": "waiting",
}
for index in range(1, 93)
]
client = FakeQueueClient(records)
pool = ModelHubClientPool(
[client], # type: ignore[list-item]
active_task_cap=100,
recent_model_reserve_slots=10,
)
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery(
{"owner/large": 40 * GIB, "owner/old": 1 * GIB},
{"owner/old": datetime(2026, 7, 1, tzinfo=timezone.utc)},
), # type: ignore[arg-type]
reference_time=datetime(2026, 8, 11, tzinfo=timezone.utc),
log=lambda _message: None,
)
self.assertEqual(1, summary["certainOomCount"])
self.assertEqual([92], [item["taskId"] for item in summary["oldOverflowTasks"]])
self.assertEqual([[1], [92]], client.stopped)
def test_stop_tasks_uses_documented_put_endpoint_and_integer_ids(self) -> None:
http = RecordingHttpClient()
client = ModelHubClient(http_client=http) # type: ignore[arg-type]
client.stop_tasks(["12", 12, 13])
self.assertEqual(
[
(
"PUT",
"/api/async/task/stop-create-contest-task",
None,
{"taskIds": [12, 13]},
)
],
http.calls,
)
def test_only_exact_size_capacity_failures_are_selected(self) -> None:
tasks = [
OwnedTask(0, 1, "owner/too-large", "Iluvatar_bi-100", "waiting"),
OwnedTask(0, 2, "owner/fits", "Iluvatar_bi-100", "waiting"),
OwnedTask(0, 3, "owner/unknown-size", "Iluvatar_bi-100", "waiting"),
OwnedTask(0, 4, "owner/unknown-gpu", "new-gpu", "waiting"),
]
selected, skipped = find_certain_oom_tasks(
tasks,
repository_sizes={
"owner/too-large": 30 * GIB,
"owner/fits": 20 * GIB,
"owner/unknown-gpu": 30 * GIB,
},
)
self.assertEqual([1], [item["taskId"] for item in selected])
self.assertEqual(1, skipped["repositorySizeUnknown"])
self.assertEqual(1, skipped["gpuCapacityUnknown"])
self.assertEqual(1, skipped["fitsKnownCapacity"])
def test_cleanup_stops_only_certain_oom_tasks_on_the_owning_account(self) -> None:
first = FakeQueueClient(
[
{"taskId": 1, "modelId": "owner/large", "gpuType": "Iluvatar_bi-100", "status": "waiting"},
{"taskId": 2, "modelId": "owner/small", "gpuType": "Iluvatar_bi-100", "status": "waiting"},
]
)
second = FakeQueueClient(
[{"taskId": 3, "modelId": "owner/large", "gpuType": "MetaX_c-500", "status": "waiting"}]
)
pool = ModelHubClientPool([first, second], active_task_cap=100) # type: ignore[list-item]
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery({"owner/large": 40 * GIB, "owner/small": 20 * GIB}), # type: ignore[arg-type]
log=lambda _message: None,
)
self.assertEqual(1, summary["certainOomCount"])
self.assertEqual(1, summary["cancelledCount"])
self.assertEqual([[1]], first.stopped)
self.assertEqual([], second.stopped)
def test_task_that_disappears_during_scan_is_not_stopped(self) -> None:
client = FakeQueueClient(
[{"taskId": 1, "modelId": "owner/large", "gpuType": "Iluvatar_bi-100", "status": "waiting"}],
disappear_on_recheck=True,
)
pool = ModelHubClientPool([client], active_task_cap=100) # type: ignore[list-item]
summary = cleanup_certain_oom_tasks(
pool,
FakeDiscovery({"owner/large": 40 * GIB}), # type: ignore[arg-type]
log=lambda _message: None,
)
self.assertEqual(1, summary["certainOomCount"])
self.assertEqual(0, summary["cancelledCount"])
self.assertEqual(1, summary["noLongerActiveCount"])
self.assertEqual([], client.stopped)
if __name__ == "__main__":
unittest.main()