Preserve speculative finish correctness across reasoning and stop strings

ReasonerGrammarObject wraps an inner grammar, but disaggregated prebuilt replay checks the wrapper current_token to avoid accepting an already accepted token twice. Track the token on the wrapper itself so reasoning grammar follows the same contract as XGrammar.

Speculative decode can accept a stop string and EOS in one step. Check stop strings before token-based EOS after sanitizing invalid token ids, and set finished_len at the matched stop position so trailing accepted tokens do not leak.

Constraint: Current branch predates upstream helper methods for locating string stop positions, so the stop-string fix is manually ported instead of cherry-picked.

Rejected: Direct cherry-pick of bbc853df46 | current schedule_batch.py lacks the upstream helper context.

Confidence: high

Scope-risk: moderate

Directive: Keep vocab-boundary sanitization before string decoding; do not move token-based EOS ahead of stop-string checks without a same-step speculative regression test.

Tested: RED/GREEN remote pytest in cjy-glm5-new for constrained current_token and stop-string speculative tests

Tested: git diff --check; py_compile for reasoner_grammar_backend.py and schedule_batch.py

Not-tested: Full scheduler/disaggregation integration suite
This commit is contained in:
laoyao0822
2026-06-27 20:36:52 +08:00
parent f3cf95c0f1
commit 132561a151
4 changed files with 188 additions and 12 deletions

View File

@@ -50,6 +50,7 @@ class ReasonerGrammarObject(BaseGrammarObject):
self.tokens_after_think_end -= 1
def accept_token(self, token: int):
self.current_token = token
if self.tokens_after_think_end >= 0:
self.grammar.accept_token(token)
self.transfer_state(token)

View File

@@ -980,20 +980,25 @@ class Req(ReqDllmMixin):
return self.surr_and_decode_ids, self.read_offset - self.surr_offset
def tail_str(self) -> str:
def _stop_match_tail_len(self, new_accepted_len: int = 1) -> int:
# Check stop strings and stop regex patterns together
if (
len(self.sampling_params.stop_strs) == 0
and len(self.sampling_params.stop_regex_strs) == 0
):
return ""
return 0
max_len_tail_str = max(
self.sampling_params.stop_str_max_len + 1,
self.sampling_params.stop_regex_max_len + 1,
self.sampling_params.stop_str_max_len + new_accepted_len,
self.sampling_params.stop_regex_max_len + new_accepted_len,
)
tail_len = min(max_len_tail_str, len(self.output_ids))
return min(max_len_tail_str, len(self.output_ids))
def tail_str(self, new_accepted_len: int = 1) -> str:
tail_len = self._stop_match_tail_len(new_accepted_len)
if tail_len == 0:
return ""
return self.tokenizer.decode(self.output_ids[-tail_len:])
def check_match_stop_str_prefix(self) -> bool:
@@ -1049,18 +1054,51 @@ class Req(ReqDllmMixin):
return False
def _check_str_based_finish(self):
def _locate_str_stop_finished_len(
self,
new_accepted_len: int,
*,
stop_str: Optional[str] = None,
stop_regex: Optional[str] = None,
) -> int:
"""Map a matched stop string/regex to output_ids length (stop included)."""
def matched(text: str) -> bool:
if stop_str is not None:
return stop_str in text
return re.search(stop_regex, text) is not None
tail_len = self._stop_match_tail_len(new_accepted_len)
start = len(self.output_ids) - tail_len
token_window = self.output_ids[start:]
# Old prefixes were checked in the previous step.
for token_count in range(
max(1, len(token_window) - new_accepted_len + 1), len(token_window)
):
if matched(self.tokenizer.decode(token_window[:token_count])):
return start + token_count
# The full tail window is already known to match by the caller.
return len(self.output_ids)
def _check_str_based_finish(self, new_accepted_len: int = 1):
if (
len(self.sampling_params.stop_strs) > 0
or len(self.sampling_params.stop_regex_strs) > 0
):
tail_str = self.tail_str()
tail_str = self.tail_str(new_accepted_len)
# Check stop strings
if len(self.sampling_params.stop_strs) > 0:
for stop_str in self.sampling_params.stop_strs:
if stop_str in tail_str or stop_str in self.decoded_text:
stop_str_in_tail = stop_str in tail_str
if stop_str_in_tail or stop_str in self.decoded_text:
self.finished_reason = FINISH_MATCHED_STR(matched=stop_str)
if stop_str_in_tail:
self.finished_len = self._locate_str_stop_finished_len(
new_accepted_len, stop_str=stop_str
)
return True
# Check stop regex
@@ -1070,6 +1108,9 @@ class Req(ReqDllmMixin):
self.finished_reason = FINISHED_MATCHED_REGEX(
matched=stop_regex_str
)
self.finished_len = self._locate_str_stop_finished_len(
new_accepted_len, stop_regex=stop_regex_str
)
return True
return False
@@ -1113,13 +1154,17 @@ class Req(ReqDllmMixin):
new_accepted_tokens = self.output_ids[-new_accepted_len:]
if self._check_token_based_finish(new_accepted_tokens):
return
# Sanitize out-of-range / NaN token ids before any decode.
if self._check_vocab_boundary_finish(new_accepted_tokens):
return
if self._check_str_based_finish():
# Stop string beats EOS/stop-token matched in the same step. Speculative
# decoding can accept multiple tokens, and token-based finish would trim
# at EOS while leaking a stop string accepted earlier in the same step.
if self._check_str_based_finish(new_accepted_len):
return
if self._check_token_based_finish(new_accepted_tokens):
return
def reset_for_retract(self):

View File

@@ -0,0 +1,69 @@
import unittest
from sglang.srt.constrained.reasoner_grammar_backend import ReasonerGrammarObject
class _InnerGrammar:
def __init__(self):
self.accepted_tokens = []
def accept_token(self, token: int):
self.accepted_tokens.append(token)
def is_terminated(self):
return False
def rollback(self, k: int):
self.accepted_tokens = self.accepted_tokens[:-k]
def allocate_vocab_mask(self, vocab_size: int, batch_size: int, device):
return None
def fill_vocab_mask(self, vocab_mask, idx: int):
return None
def move_vocab_mask(self, vocab_mask, device):
return vocab_mask
@property
def apply_vocab_mask(self):
return None
def copy(self):
ret = _InnerGrammar()
ret.accepted_tokens = list(self.accepted_tokens)
return ret
@property
def finished(self):
return False
class TestReasonerGrammarCurrentToken(unittest.TestCase):
def test_wrapper_tracks_current_token_for_disagg_prebuilt_dedup(self):
inner = _InnerGrammar()
grammar = ReasonerGrammarObject(inner, think_end_id=7)
grammar.maybe_init_reasoning(True)
grammar.accept_token(10) # still in thinking; inner grammar is untouched
self.assertEqual(grammar.current_token, 10)
self.assertEqual(inner.accepted_tokens, [])
grammar.accept_token(7) # exits thinking
self.assertEqual(grammar.current_token, 7)
self.assertEqual(inner.accepted_tokens, [])
grammar.accept_token(58) # generation token accepted by inner grammar
self.assertEqual(grammar.current_token, 58)
self.assertEqual(inner.accepted_tokens, [58])
# Mirrors disaggregation/decode_schedule_batch_mixin.py:process_prebuilt.
# Once current_token is tracked on the wrapper, a re-prebuilt request
# skips re-accepting the already accepted token.
if grammar.current_token is None:
grammar.accept_token(58)
self.assertEqual(inner.accepted_tokens, [58])
if __name__ == "__main__":
unittest.main()

View File

@@ -0,0 +1,61 @@
import unittest
from array import array
from sglang.srt.managers.schedule_batch import Req
from sglang.srt.sampling.sampling_params import SamplingParams
STOP_ID = 1
EOS_ID = 2
ID_TO_TEXT = {
STOP_ID: "STOP",
EOS_ID: "",
**{i: chr(ord("a") + i % 26) for i in range(10, 40)},
}
class _FakeTokenizer:
eos_token_id = EOS_ID
additional_stop_token_ids = None
def decode(self, ids):
return "".join(ID_TO_TEXT[int(i)] for i in ids)
class _NormalizeTokenizer:
def encode(self, text, add_special_tokens=False):
return list(range(len(text)))
def _make_req(output_ids, *, stop=None, eos_token_ids=frozenset()):
sampling_params = SamplingParams(max_new_tokens=1000, stop=stop)
sampling_params.normalize(tokenizer=_NormalizeTokenizer())
req = Req(
rid="r",
origin_input_text="",
origin_input_ids=array("q", [0]),
sampling_params=sampling_params,
eos_token_ids=set(eos_token_ids),
vocab_size=10_000,
)
req.tokenizer = _FakeTokenizer()
req.output_ids = array("q", output_ids)
return req
class TestStopStrSpeculative(unittest.TestCase):
def test_stop_str_wins_over_eos_in_same_spec_step(self):
# A speculative step may accept both the stop string and EOS. The stop
# string must finish first so finished_len trims at STOP instead of EOS.
req = _make_req([10, 11, STOP_ID, EOS_ID], stop=["STOP"], eos_token_ids={EOS_ID})
req.check_finished(new_accepted_len=4)
self.assertTrue(req.finished())
self.assertEqual(req.finished_reason.matched, "STOP")
self.assertEqual(req.finished_len, 3)
self.assertEqual(list(req.output_ids_through_stop), [10, 11, STOP_ID])
if __name__ == "__main__":
unittest.main()