[xpu] disable cudagraph for xpu platform

[chaojun-zhang]

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

When running certain models in torch.compile mode, the system might try to use CUDA Graph-related code. This isn't supported on XPU platforms, so we've disabled it here.

Test Plan

VLLM_USE_V1=1 python examples/offline_inference/audio_language.py -m granite_speech

Test Result

Without this PR:
lora_b_stacked_2_ = None
File "/home/chaojun/vllm/vllm/compilation/cuda_piecewise_backend.py", line 164, in call
cudagraph = torch.cuda.CUDAGraph()
File "/home/chaojun/.local/lib/python3.10/site-packages/torch/cuda/graphs.py", line 74, in new
return super().new(cls, keep_graph)
File "/home/chaojun/.local/lib/python3.10/site-packages/torch/_utils.py", line 996, in err_fn
raise RuntimeError(f"Tried to instantiate dummy base class {class_name}")
RuntimeError: Tried to instantiate dummy base class CUDAGraph

With this PR:

Adding requests: 100%|███████████████████████████████████████████████████████████████████| 1/1 [00:10<00:00, 10.00s/it]
Fetching 25 files: 100%|████████████████████████████████████████████████████████████| 25/25 [00:00<00:00, 23101.48it/s]
Processed prompts: 100%|███████████| 1/1 [00:03<00:00, 3.68s/it, est. speed input: 61.98 toks/s, output: 12.50 toks/s]
the first words i spoke in the original phonograph a little piece of practical poetry mary had a little lamb its fleece was white as snow and everywhere that mary went the lamb was sure to go

(Optional) Documentation Update

[gemini-code-assist]

Code Review

This pull request disables CUDA graphs for the XPU platform, preventing a runtime crash. While this is a valid fix, consider implementing a dedicated XpuPiecewiseBackend or using a platform-agnostic backend for XPU to improve long-term stability.

[gemini-code-assist]

Disabling CUDA graphs for the XPU platform prevents a runtime crash, which is a valid fix. However, the system attempts to use a CUDA-specific backend (cuda_piecewise_backend.py) on the XPU platform. Consider implementing a dedicated XpuPiecewiseBackend or using a platform-agnostic backend for XPU to improve long-term stability.

[github-actions]

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