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[#15022][fix] Guided decoding (xgrammar) + EAGLE-3 + draft_len_schedule reaching 0 crashes during CUDA graph capture, "bitmask must have the same batch size as logits" #15023

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Merged
achartier merged 2 commits into from
Jun 11, 2026
Merged

[#15022][fix] Guided decoding (xgrammar) + EAGLE-3 + draft_len_schedule reaching 0 crashes during CUDA graph capture, "bitmask must have the same batch size as logits" #15023

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chungen04 Jun 5, 2026
0e4f0b4
modified for pre-commit hook formatting
chungen04 Jun 8, 2026
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25 changes: 19 additions & 6 deletions tensorrt_llm/_torch/pyexecutor/guided_decoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -259,8 +259,12 @@ def _build(self, requests: GuidedRequests) -> List[Tuple[int, str]]:
matcher.fill_next_token_bitmask(self.bitmask_host, offset)
self.token_mask_host[offset] = 1
self.num_guided_tokens[slot] += 1
# Process draft tokens
for i, tid in enumerate(req.draft_tokens, 1):
# Process draft tokens. Bound by the layout's draft length:
# the new_tokens buffer always holds the static max, but only
# `max_num_draft_tokens` slots are reserved this iteration.
for i, tid in enumerate(
req.draft_tokens[:requests.max_num_draft_tokens],
1):
accepted = matcher.accept_token(tid)
if not accepted:
break
Expand Down Expand Up @@ -332,9 +336,13 @@ def _apply_bitmask(self,
d2t=d2t)

@nvtx_range("GuidedDecoder.add_batch")
def add_batch(self, scheduled_requests: ScheduledRequests) -> None:
def add_batch(self,
scheduled_requests: ScheduledRequests,
runtime_draft_len: Optional[int] = None) -> None:
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num_draft_tokens = (self.max_num_draft_tokens
if runtime_draft_len is None else runtime_draft_len)
self.requests = GuidedRequests.from_scheduled_requests(
scheduled_requests, self.max_num_draft_tokens)
scheduled_requests, num_draft_tokens)
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@nvtx_range("GuideDecoder.build")
def build(self) -> List[Tuple[int, str]]:
Expand Down Expand Up @@ -470,9 +478,14 @@ def __init__(self,
@nvtx_range("GuidedDecoder.add_batch")
def add_batch(self,
scheduled_requests: ScheduledRequests,
new_tokens: Optional[torch.Tensor] = None) -> None:
new_tokens: Optional[torch.Tensor] = None,
runtime_draft_len: Optional[int] = None) -> None:
# See GuidedDecoder.add_batch: the layout must follow the runtime draft
# length so the captured graph's bitmask matches the target logits.
num_draft_tokens = (self.max_num_draft_tokens
if runtime_draft_len is None else runtime_draft_len)
self.requests = GuidedRequests.from_scheduled_requests(
scheduled_requests, self.max_num_draft_tokens)
scheduled_requests, num_draft_tokens)
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if new_tokens is not None:
self.new_tokens.copy_(new_tokens.squeeze(-1), non_blocking=True)
self.queue.put((self.requests, new_tokens is not None))
Expand Down
6 changes: 4 additions & 2 deletions tensorrt_llm/_torch/pyexecutor/model_engine.py
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Expand Up @@ -2633,8 +2633,10 @@ def _prepare_tp_inputs(

# Must be before the update of py_batch_idx
if self.guided_decoder is not None:
self.guided_decoder.add_batch(scheduled_requests,
new_tokens=new_tokens_device)
self.guided_decoder.add_batch(
scheduled_requests,
new_tokens=new_tokens_device,
runtime_draft_len=self.runtime_draft_len)

if self._can_use_incremental_update(scheduled_requests,
new_tokens_device,
Expand Down
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