[Bugfix] Fix torch.compile error for DP + MoE on CPU Backend

[kzwrime]

Purpose

Fix #31648 (torch.compile fails for MoE models on CPU backend with -dp 2).

Fix the error by reordering has_flashinfer_trtllm_fused_moe() in post_quant_allgather.

Test Plan

vllm serve "Qwen/Qwen1.5-MoE-A2.7B-Chat" -dp 2

Test Result

The service can start successfully.

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• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
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[gemini-code-assist]

Code Review

This pull request effectively resolves a torch.compile error that occurred with MoE models on CPU backends using data parallelism. The core of the fix is in vllm/model_executor/layers/fused_moe/layer.py, where the conditions for the post_quant_allgather flag are reordered. By moving the has_flashinfer_trtllm_fused_moe() check to the end of the expression, the change leverages short-circuiting to prevent torch.compile from tracing this non-traceable function on CPU platforms. This is a clean and correct solution. The accompanying changes in base_device_communicator.py and xpu_communicator.py are necessary API updates to plumb the extra_tensors parameter, which is part of the feature enabled by post_quant_allgather. These changes are implemented safely and do not pose a risk to other backends. The pull request is well-executed and improves the framework's robustness.