[Bugfix] V1 Fix the cursor leakage issue during request scheduling. (#21173)

Signed-off-by: CLFutureX <775523362@qq.com>
This commit is contained in:
PiteXChen 2025-08-05 09:34:10 +08:00 committed by GitHub
parent bdcb42e45d
commit 2dffac464c
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 100 additions and 3 deletions

View File

@ -1307,13 +1307,18 @@ def create_requests_with_priority(
mm_positions: Optional[list[PlaceholderRange]] = None, mm_positions: Optional[list[PlaceholderRange]] = None,
max_tokens: int = 16, max_tokens: int = 16,
stop_token_ids: Optional[list[int]] = None, stop_token_ids: Optional[list[int]] = None,
prompt_logprobs: Optional[int] = None): prompt_logprobs: Optional[int] = None,
request_ids: Optional[list[str]] = None):
"""Create requests with specified priorities and arrival times.""" """Create requests with specified priorities and arrival times."""
assert len(priorities) == num_requests assert len(priorities) == num_requests
if arrival_times is not None: if arrival_times is not None:
assert len(arrival_times) == num_requests assert len(arrival_times) == num_requests
else: else:
arrival_times = [float(i) for i in range(num_requests)] arrival_times = [float(i) for i in range(num_requests)]
if request_ids is not None:
assert len(request_ids) == num_requests
else:
request_ids = [f"{i}" for i in range(num_requests)]
sampling_params = SamplingParams(ignore_eos=False, sampling_params = SamplingParams(ignore_eos=False,
max_tokens=max_tokens, max_tokens=max_tokens,
@ -1328,7 +1333,7 @@ def create_requests_with_priority(
mm_position = None mm_position = None
mm_inputs = None mm_inputs = None
request = Request( request = Request(
request_id=f"{i}", request_id=request_ids[i],
prompt_token_ids=[i] * num_tokens, prompt_token_ids=[i] * num_tokens,
sampling_params=sampling_params, sampling_params=sampling_params,
pooling_params=None, pooling_params=None,
@ -1829,3 +1834,91 @@ def test_schedule_skip_tokenizer_init_structured_output_request():
assert len(output.scheduled_new_reqs) == 0 assert len(output.scheduled_new_reqs) == 0
assert len(scheduler.running) == 0 assert len(scheduler.running) == 0
assert len(scheduler.waiting) == 1 assert len(scheduler.waiting) == 1
def test_priority_scheduling_preemption_victim_iterator_order():
"""Test that the scheduling order is maintained after
preempting lower-priority requests."""
scheduler = create_scheduler_with_priority(
max_num_batched_tokens=200,
num_blocks=9,
)
# Add three priority requests first.
priority_requests = create_requests_with_priority(
num_requests=3,
priorities=[3, 4, 5],
arrival_times=[1.0, 2.0, 3.0],
num_tokens=15,
request_ids=["1", "2", "3"],
)
for request in priority_requests:
scheduler.add_request(request)
# After scheduling, transfer from the waiting queue to the running queue.
# At this time, 3 blocks have been allocated, and 5 available blocks remain.
output = scheduler.schedule()
model_output = ModelRunnerOutput(
req_ids=[req.request_id for req in priority_requests],
req_id_to_index={
req.request_id: i
for i, req in enumerate(priority_requests)
},
sampled_token_ids=[[15] for _ in priority_requests],
spec_token_ids=None,
logprobs=None,
prompt_logprobs_dict={},
pooler_output=[],
)
scheduler.update_from_output(output, model_output)
# Add tow high priority requests.
high_priority_requests = create_requests_with_priority(
num_requests=2,
priorities=[1, 2],
arrival_times=[4.0, 5.0],
num_tokens=16,
request_ids=["4", "5"],
)
for request in high_priority_requests:
scheduler.add_request(request)
# After scheduling, transfer the two high-priority requests from
# the waiting queue to the running queue.
# the IDs of the requests in the running queue are: 1, 2, 3, 4, 5.
# At this time, 3+2 blocks have been allocated,
# and 3 available blocks remain.
output = scheduler.schedule()
merge_requests = priority_requests + high_priority_requests
model_output = ModelRunnerOutput(
req_ids=[req.request_id for req in merge_requests],
req_id_to_index={
req.request_id: i
for i, req in enumerate(merge_requests)
},
sampled_token_ids=[[1] for _ in merge_requests],
spec_token_ids=None,
logprobs=None,
prompt_logprobs_dict={},
pooler_output=[],
)
scheduler.update_from_output(output, model_output)
# At this time, the request with the lowest priority
# (request.id = 2) will be preempted, freeing up 2 blocks,
# which exactly meets the resource allocation requirements
# for request.id = 4 and request.id = 5.
output = scheduler.schedule()
# Should schedule the new request without preemption.
assert len(scheduler.running) == 4 #
assert len(scheduler.waiting) == 1 #
running_priorities = [req.priority for req in scheduler.running]
running_req_ids = [req.request_id for req in scheduler.running]
assert running_priorities == [3, 4, 1, 2]
assert running_req_ids == ["1", "2", "4", "5"]
assert scheduler.waiting.peek_request().priority == 5

View File

@ -257,7 +257,11 @@ class Scheduler(SchedulerInterface):
self.running, self.running,
key=lambda r: (r.priority, r.arrival_time), key=lambda r: (r.priority, r.arrival_time),
) )
self.running.remove(preempted_req) preempted_index = self.running.index(preempted_req)
if preempted_index <= req_index:
req_index -= 1
scheduled_running_reqs.remove(preempted_req)
self.running.pop(preempted_index)
else: else:
preempted_req = self.running.pop() preempted_req = self.running.pop()