FA4 attention for ViT

[zhandaz]

FA4 Integration

(1) Support fa4 in vllm.

From low-level to high-level:

1. Add FLASH_ATTN_CUTE (FA4 / flash_attn.cute) to vllm/v1/attention/backends/registry.py (AttentionBackendEnum).
2. Create a new file vllm/v1/attention/backends/fa4_utils.py, for the utils / imports for fa4 (keep imports lazy).
3. Register the new backend in vllm/platforms/cuda.py (FA4 is Blackwell-only (CC 10.x) and opt-in via --mm-encoder-attn-backend FLASH_ATTN_CUTE; default remains FA2/3 or Torch SDPA).
4. Add the fa4 custom op under vllm/v1/attention/ops/vit_attn_wrappers.py.
5. Update vllm/model_executor/layers/attention/mm_encoder_attention.py to add another _forward_impl method for fa4 (FLASH_ATTN_CUTE).
6. Update vllm/model_executor/models/qwen3_vl.py and (optionally) qwen2_5_vl.py to accept FLASH_ATTN_CUTE and compute max_seqlen for it.

Notes:

• FA4 (flash_attn.cute) is only considered on Blackwell (compute capability 10.x) in this vLLM fork.
• To force FA4 for ViT/MM encoder attention (Blackwell only): --mm-encoder-attn-backend FLASH_ATTN_CUTE.

(2) Do the kernel_warmup in vllm.

• Add a FA4 ViT warmup in vllm/model_executor/warmup/kernel_warmup.py (see vllm/model_executor/warmup/fa4_warmup.py).
• Scope: Qwen3-VL / Qwen3-VL-MoE vision transformer only, Blackwell-only, and only when --mm-encoder-attn-backend FLASH_ATTN_CUTE is set.
• Candidate seqlens (only varying seqlen): [64, 256, 576, 1024, 2304, 4096, 9216, 16384, 36864, 65536] (filtered by vision_config.num_position_embeddings if smaller).

(3) Minor fixes for FA4 integration.

• In vllm/model_executor/layers/rotary_embedding/common.py, there is a logic of if find_spec("flash_attn") is not None:
  However, flash_attn original package is actually not installed, not flash_attn.cute is installed.
  Therefore, minor fix is needed for the import error.

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[wangshangsam]

Could you run ruff check and ruff format (you can see that the pre-commit action is failing)? Otherwise, LGTM

[zhandaz]

Sure. Let me fix it.