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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 7, 02:45 UTC

Fix CUDA graph decode capture crash in AITER FlashAttention (#36042)

Signed-off-by: Martin Yuan <myuan@meta.com> Co-authored-by: Martin Yuan <myuan@meta.com>

Mengtao (Martin) Yuan committed Mar 6, 2026 at 18:12 UTC 1a9718085c7980443558db1ff4160c58096a3f0e
1 file changed +3 -4
vllm/v1/attention/backends/rocm_aiter_fa.py
+3 -4
@@ -1152,11 +1152,10 @@ class AiterFlashAttentionImpl(AttentionImpl):
1152 decode_max_query_len = attn_metadata.decode_metadata.max_query_len
1153
1154 # Use unified_attention for speculative decoding (multi-token)
1155 - # or when sliding window is enabled
1156 - if self.sliding_window[0] != -1 or decode_max_query_len > 1:
1155 + if decode_max_query_len > 1:
1156 assert not rocm_aiter_ops.is_shuffle_kv_cache_enabled(), (
1158 - "Shuffle KV cache layout is not supported with sliding "
1159 - "window or speculative decoding (multi-token decode)."
1157 + "Shuffle KV cache layout is not supported with "
1158 + "speculative decoding (multi-token decode)."
1159 )
1160 from aiter.ops.triton.unified_attention import (
1161 unified_attention,