[Perf] Skip/shrink all_token_ids copy in scheduler for non-async and V2 runner

[amanchugh89]

Summary

CachedRequestData.all_token_ids is read in exactly one place — the V1 GPU
model runner, and only when async scheduling is enabled
(vllm/v1/worker/gpu_model_runner.py, gated on self.use_async_scheduling).
There it restores a resumed request's output tokens after a gap step:

if self.use_async_scheduling and num_output_tokens > 0:
    resumed_token_ids = req_data.all_token_ids[req_id]
    req_state.output_token_ids = resumed_token_ids[-num_output_tokens:]

Previously _make_cached_request_data() copied the full token history
(req.all_token_ids.copy(), prompt + output) for every resumed request, and
SchedulerOutput is then msgpack-serialized to every worker. For the V2 model
runner and for the common non-async path (single-GPU, TP, most DP), that payload
is built and shipped but never read.

Changes

vllm/v1/core/sched/scheduler.py:

if (
    not self.use_v2_model_runner
    and not scheduled_in_prev_step
    and self.scheduler_config.async_scheduling
):
    assert req.num_output_placeholders == 0
    num_out = req.num_output_tokens
    if num_out > 0:
        all_token_ids[req_id] = req._all_token_ids[-num_out:]

• Skip the dict entirely for the V2 runner and when async scheduling is off
  (nothing reads it in those cases).
• Copy only the request's output tokens (_all_token_ids[-num_out:]) instead of
  the full prompt+output history — this is exactly what the runner restores via
  resumed_token_ids[-num_output_tokens:].
• A request resumed here was not scheduled in the previous step, so it has no
  in-flight placeholder tokens; assert that and slice by num_output_tokens.

Also fixes the stale CachedRequestData.all_token_ids docstring (it referenced
a "connector"; the only reader is the V1 model runner under async scheduling).

Relationship to #34029

This finishes the abandoned PR #34029 (closed by its author, not merged) and
folds in the review feedback it never landed: @njhill's use_v2_model_runner
guard and the observation that resumed requests carry no placeholders (assert +
slice by num_output_tokens), plus copying only the output-side tokens. Happy
to close this if it's not wanted given the V2 model runner migration.

Tests

CPU (tests/v1/core/test_scheduler.py is cpu_test):

python -m pytest tests/v1/core/test_scheduler.py -v          # 103 passed

GPU end-to-end (single NVIDIA T4, Qwen/Qwen3-0.6B) — the only test exercising
the V1 runner consuming all_token_ids under async scheduling + preemption,
with greedy check_outputs_equal across all executor / preemption / async /
prefill-chunking combinations:

python -m pytest tests/v1/e2e/general/test_async_scheduling.py::test_without_spec_decoding -v
# 1 passed in 746.65s

• Added test_cached_request_data_resumed_all_token_ids_async covering the
  resumed payload (output tokens only, prompt prefix excluded).
• Updated two preemption/resumption tests to expect an empty all_token_ids in
  the default (non-async) config.

ruff check and ruff format clean on all changed files.

AI assistance

Developed with AI assistance (Claude). Every changed line was reviewed by the
submitter, who understands and can defend the change end-to-end.
I have tested manually on T4 GPU, and the code was worked on plan mode so the code created by claude but I have validated to the best of my knowledge.

[amanchugh89]

cc @njhill — this revisits the area of #34029 (closed) with your review feedback folded in: the not use_v2_model_runner guard, copying only the request's output tokens, and asserting that a resumed request carries no in-flight placeholders (so we slice by num_output_tokens). It also gates on async_scheduling, since gpu_model_runner.py is the only reader and it's behind that flag.

Added a focused unit test for the resumed payload and validated end-to-end on a T4 (tests/v1/e2e/general/test_async_scheduling.py::test_without_spec_decoding passes, 1 passed in ~12m). Happy to close if this isn't worth pursuing given the V2 model runner migration — just wanted to finish the idea with the feedback addressed.

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[njhill]

Thanks @amanchugh89, I think this is a good perf fix to make.

I have pushed some simplifications, I don't think we need to optimize the MRV1 case; it's probably better to keep the full token ids in the resume case since I think this may be used by some OOT plugins.

[amanchugh89]

Thanks @amanchugh89, I think this is a good perf fix to make.

I have pushed some simplifications, I don't think we need to optimize the MRV1 case; it's probably better to keep the full token ids in the resume case since I think this may be used by some OOT plugins.

Makes sense — keeping full token ids on the V1 path for OOT plugin safety and only skipping it for V2 is cleaner than gating on async. Thanks @njhill for the simplifications and the review 🙏