[Bugfix] Disable CG for Whisper+FA2

[NickLucche]

Temporary fix to address #33091 for a tentative v0.15.0 release. As the issue is purely in accuracy and does not produce a crash, I believe it's better to patch it until fixed as to not mislead users deploying Whisper.

This PR disables CG for encoder-decoder models when FA2 is detected.

Test with

python -m pytest -v -s -x tests/entrypoints/openai/test_transcription_validation_whisper.py

# On FA2, with following patch/diff
--- a/tests/entrypoints/openai/test_transcription_validation_whisper.py
+++ b/tests/entrypoints/openai/test_transcription_validation_whisper.py
@@ -16,7 +16,7 @@ import soundfile as sf
 from ...utils import RemoteOpenAIServer

 MODEL_NAME = "openai/whisper-large-v3-turbo"
-SERVER_ARGS = ["--enforce-eager"]
+SERVER_ARGS = ["--attention-config.flash_attn_version=2"]

or with manual script from issue (failing on master):

from vllm.config import AttentionConfig
from vllm import LLM, SamplingParams
from vllm.config.compilation import CompilationConfig, CompilationMode, CUDAGraphMode
from vllm.assets.audio import AudioAsset

def main():
    model_name = "openai/whisper-large-v3-turbo"

    llm = LLM(
        model=model_name,
        tensor_parallel_size=1,
        enforce_eager=False,
        attention_config=AttentionConfig(
            flash_attn_version=2,
        ),
    )
    params = SamplingParams(temperature=0.0, max_tokens=3)
    outputs = llm.generate(
        [
            {
            "prompt": "<|startoftranscript|><|en|><|transcribe|><|notimestamps|>",
            "multi_modal_data": {
                "audio": AudioAsset("mary_had_lamb").audio_and_sample_rate,
            },
        },
        ],
        sampling_params=params,
    )
    for o in outputs:
        generated_text = o.outputs[0].text
        print("output:", generated_text)
        assert "The first" in generated_text

if __name__ == "__main__":
    main()

[gemini-code-assist]

Code Review

This pull request introduces a temporary but effective fix for an accuracy issue observed with FlashAttention2 (FA2) when used with encoder-decoder models, specifically Whisper, as detailed in issue #33091. The change correctly disables CUDA graphs for this specific combination, mitigating the reported accuracy problems. The implementation is clear, uses logger.warning_once for informative logging, and appears to handle edge cases appropriately, such as when FlashAttention is not available or when the global CUDA graph mode is already set. This is a well-targeted solution to a critical accuracy bug.