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sgl-project--sglang/python/sglang/test/scripted_runtime_chunked_helpers.py
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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

161 lines
5.0 KiB
Python

from __future__ import annotations
from typing import Any, Dict, List
DEFAULT_CHUNK_SIZE: int = 256
DEFAULT_MAX_STEPS: int = 400
VERY_LONG_PROMPT_LEN: int = 8 * DEFAULT_CHUNK_SIZE
SMALL_MODEL: str = "Qwen/Qwen3-0.6B"
def base_engine_kwargs(
*,
model_path: str = SMALL_MODEL,
chunked_prefill_size: int = DEFAULT_CHUNK_SIZE,
**overrides: Any,
) -> Dict[str, Any]:
kwargs: Dict[str, Any] = dict(
model_path=model_path,
chunked_prefill_size=chunked_prefill_size,
)
kwargs.update(overrides)
return kwargs
def run_until(handle, predicate, *, max_steps: int = DEFAULT_MAX_STEPS):
for _ in range(max_steps):
if predicate(handle):
return
yield
raise AssertionError(
f"run_until: predicate never satisfied after {max_steps} steps "
f"(handle rid={handle.rid!r}, finished={handle.finished})"
)
def run_until_finished(handle, *, max_steps: int = DEFAULT_MAX_STEPS):
yield from run_until(handle, lambda h: h.finished, max_steps=max_steps)
def run_until_all_finished(handles: List[Any], *, max_steps: int = DEFAULT_MAX_STEPS):
done = [False] * len(handles)
for _ in range(max_steps):
for i, h in enumerate(handles):
done[i] = done[i] or h.finished
if all(done):
return
yield
raise AssertionError(
f"run_until_all_finished: not all reqs finished after {max_steps} "
f"steps (finished={done})"
)
def warmup_radix(t, prompt_tokens: List[int], *, max_steps: int = DEFAULT_MAX_STEPS):
assert prompt_tokens, "warmup_radix needs a non-empty prompt"
token = prompt_tokens[0]
assert all(
x == token for x in prompt_tokens
), "warmup_radix supports only uniform prompts"
handle = t.start_req(
prompt_len=len(prompt_tokens), max_new_tokens=1, prompt_token=token
)
yield from run_until_finished(handle, max_steps=max_steps)
BALLAST_MAX_NEW_TOKENS: int = 30000
SMALL_KV_POOL_MAX_TOTAL_TOKENS: int = 4096
SMALL_KV_POOL_BALLAST_MAX_NEW_TOKENS: int = 512
SMALL_KV_POOL_BALLAST_PROMPT_LEN: int = 1536
def exhaust_row_pool(t, *, leave_rows: int, max_steps: int = DEFAULT_MAX_STEPS):
target: int = t.scheduler.req_to_token_pool.available_size() - leave_rows
if target <= 0:
return
for _ in range(target):
t.start_req(
prompt_len=1, max_new_tokens=BALLAST_MAX_NEW_TOKENS, ignore_eos=True
)
for _ in range(max_steps):
if t.scheduler.req_to_token_pool.available_size() <= leave_rows:
return
yield
raise AssertionError(
f"exhaust_row_pool: ballast reqs never filled the row pool down to "
f"leave_rows={leave_rows} after {max_steps} steps "
f"(available_size={t.scheduler.req_to_token_pool.available_size()})"
)
LIFECYCLE_STAGES = (
"first_chunk",
"last_chunk",
"first_decode",
"mid_decode",
"last_decode",
)
def advance_to_nth_chunk(r, target_chunk: int, *, max_steps: int = DEFAULT_MAX_STEPS):
# Drive until the hook has recorded `target_chunk` chunked-prefill batches.
# chunks_done is accumulated from on_run_batch (every forward batch), so it
# never misses a chunk the way sampling the instantaneous is_chunking flag
# once per yield can: on the step the req leaves chunked_req, is_chunking is
# already False, so `seen` undercounted and the req could race to completion
# on slower CI before the loop caught up.
for _ in range(max_steps):
assert not r.finished, f"req finished before reaching chunk {target_chunk}"
if r.chunks_done >= target_chunk:
return
yield
raise AssertionError(
f"never reached chunk {target_chunk} (chunks_done={r.chunks_done})"
)
def advance_to_decode_step(
r, target_output_len: int, *, max_steps: int = DEFAULT_MAX_STEPS
):
for _ in range(max_steps):
assert (
not r.finished
), f"req finished before reaching decode step {target_output_len}"
req = r.req
if req is not None and len(req.output_ids) >= target_output_len:
return
yield
raise AssertionError(f"never reached decode step {target_output_len}")
def advance_to_lifecycle_stage(
r,
stage: str,
*,
num_middle_chunks: int,
max_new_tokens: int,
max_steps: int = DEFAULT_MAX_STEPS,
):
if stage == "first_chunk":
yield from advance_to_nth_chunk(r, 1, max_steps=max_steps)
elif stage == "last_chunk":
yield from advance_to_nth_chunk(r, num_middle_chunks, max_steps=max_steps)
elif stage == "first_decode":
yield from advance_to_decode_step(r, 1, max_steps=max_steps)
elif stage == "mid_decode":
yield from advance_to_decode_step(
r, max(1, max_new_tokens // 2), max_steps=max_steps
)
elif stage == "last_decode":
yield from advance_to_decode_step(r, max_new_tokens - 1, max_steps=max_steps)
else:
raise AssertionError(f"unknown lifecycle stage {stage!r}")