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[bugfix][deepseek] fix flashmla kernel selection #25956

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Merged
merged 2 commits into from
Sep 30, 2025
Merged

[bugfix][deepseek] fix flashmla kernel selection #25956

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095fd64
fix flashmla kernel selection
youkaichao Sep 30, 2025
cc1839f
fix flashmla kernel selection
youkaichao Sep 30, 2025
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2 changes: 1 addition & 1 deletion vllm/attention/ops/flashmla.py
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Original file line number Diff line number Diff line change
Expand Up @@ -136,7 +136,7 @@ def flash_mla_with_kvcache(
descale_k is None
), "descale_q and descale_k should be both None or both not None"

if (descale_q is not None) and (descale_k is not None):
if indices is None and q.element_size() == 1:
out, softmax_lse = torch.ops._flashmla_extension_C.fwd_kvcache_mla_fp8(
q, k_cache, head_dim_v, cache_seqlens, block_table, softmax_scale,
causal, tile_scheduler_metadata, num_splits, descale_q, descale_k)
Comment on lines +139 to 142
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critical

This change correctly identifies FP8 tensors using q.element_size() == 1. However, it introduces a potential issue where the FP8 kernel could be called without the necessary scaling factors. If q is an FP8 tensor but descale_q is None, fwd_kvcache_mla_fp8 would be called with None for descale_q and descale_k. This would likely cause a crash or incorrect computation within the underlying C++ kernel, as FP8 operations require these scaling factors.

To make this function more robust, I suggest adding an assertion to ensure that descale_q and descale_k are provided when q is an FP8 tensor.

    if indices is None and q.element_size() == 1:
        assert descale_q is not None, (
            "descale_q and descale_k must be provided for fp8 attention")
        out, softmax_lse = torch.ops._flashmla_extension_C.fwd_kvcache_mla_fp8(
            q, k_cache, head_dim_v, cache_seqlens, block_table, softmax_scale,
            causal, tile_scheduler_metadata, num_splits, descale_q, descale_k)

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