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Fix issue 19717 by making qo_indptr uniform strided instead of packed (#19807)

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kpham-sgl
2026-03-04 15:27:10 -08:00
committed by GitHub
parent 28c931e1a5
commit 376dfb03f7
1 changed files with 8 additions and 2 deletions
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python/sglang/srt/layers/attention/triton_backend.py
+8 -2
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@@ -761,9 +761,15 @@ class TritonAttnBackend(AttentionBackend):
mask_indptr[1 : bs + 1] = torch.cumsum(seq_mask_len, dim=0) mask_indptr[1 : bs + 1] = torch.cumsum(seq_mask_len, dim=0)
elif forward_mode.is_draft_extend(include_v2=True): elif forward_mode.is_draft_extend(include_v2=True):
seq_lens = seq_lens[:bs] seq_lens = seq_lens[:bs]
accept_lens = spec_info.accept_length[:bs] num_tokens_per_bs = self.speculative_num_steps + 1
qo_indptr = self.qo_indptr[: bs + 1] qo_indptr = self.qo_indptr[: bs + 1]
qo_indptr[1 : bs + 1] = torch.cumsum(accept_lens, dim=0) qo_indptr[: bs + 1] = torch.arange(
0,
bs * num_tokens_per_bs + 1,
step=num_tokens_per_bs,
dtype=torch.int32,
device=self.device,
)
kv_indptr = self.kv_indptr[: bs + 1] kv_indptr = self.kv_indptr[: bs + 1]
kv_indptr[1 : bs + 1] = torch.cumsum(seq_lens, dim=0) kv_indptr[1 : bs + 1] = torch.cumsum(seq_lens, dim=0)
kv_indices = self.cuda_graph_kv_indices kv_indices = self.cuda_graph_kv_indices