[Attention] remove decode wrapper of flashinfer

[happierpig]

Purpose

This PR removes the decode wrapper of the FlashInfer backend in V1 to simplify code paths and improve maintenance. As use_tensor_cores is always enabled for batch decode requests for better performance (

vllm/vllm/v1/attention/backends/flashinfer.py

Line 380 in aae725a

use_tensor_cores=True,

), the backend kernels are always dispatched into FA2 prefill kernels in FlashInfer (https://github.com/flashinfer-ai/flashinfer/blob/2bd914460c08c3d26093165b117fb9089f857bed/flashinfer/decode.py#L1018). Thus, using either DecodeWrapper or PrefillWrapper is theoretically equivalent.

In the future, both prefill and decode could be batched and executed within a single kernel call for a unified kernel (as proposed in flashinfer-ai/flashinfer#1137).

cc @heheda12345 for #24856. This PR is compatible with current stable FlashInfer.

Test Plan

Test Result

perf benchmark:

The ~2% perf degrade potentially due to the lightly higher overhead of plan function of BatchPrefillWrapper, which should be minimal when using fast_decode_plan (

vllm/vllm/v1/attention/backends/flashinfer.py

Line 978 in aae725a

def fast_plan_decode(

) in cuda graph.

---

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[gemini-code-assist]

Code Review

This pull request aims to simplify the FlashInfer backend by removing the DecodeWrapper and using the PrefillWrapper for both prefill and decode operations. This is a good simplification that improves code maintenance. However, I've identified a critical issue in the fast_plan_decode function where the arguments passed to the plan method are incorrect. This will lead to a runtime error and needs to be fixed.