[bugfix]Enable dispatch_ffn_combine feature for qwen3.5

[asunxiao]

What this PR does / why we need it?

Qwen3.5 Moe supports enabling the dispatch_ffn_combine fusion operator.

Fix problem: In the w8a8 quantization scene, Qwen3.5 model's config.json lacks the quantize field. The previous logic strictly relied on quant_type == "w8a8_dynamic" to enable VLLM_ASCEND_ENABLE_FUSED_MC2. This caused the dispatch_ffn_combine fusion operator to fail to activate even when the environment variable was set.

Enable dispatch_ffn_combine fusion operator for BF16 scenarios.

Does this PR introduce any user-facing change?

How was this patch tested?

• vLLM version: v0.16.0
• vLLM main: vllm-project/vllm@4034c3d

[github-actions]

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[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enables the dispatch_ffn_combine fusion operator, specifically for Qwen3.5 Mixture of Experts (MoE) models. The change removes a previous dependency on a specific quantization type (w8a8_dynamic) for the fused_mc2_enable flag, thereby broadening the applicability of this performance optimization. This aims to improve the efficiency and compatibility of MoE models on Ascend hardware.

Highlights

• Feature Enablement: Enabled the dispatch_ffn_combine fusion operator for Qwen3.5 MoE models.
• Quantization Restriction Removal: Removed the w8a8_dynamic quantization type restriction for the fused_mc2_enable condition, allowing broader use of the dispatch_ffn_combine feature.

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Changelog

• vllm_ascend/ascend_forward_context.py
  • Removed the quant_type variable definition.
  • Updated the fused_mc2_enable condition to no longer check for a specific quantization type.

Activity

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[gemini-code-assist]

Code Review

This pull request aims to enable the dispatch_ffn_combine fusion operator for Qwen3.5 MoE models by removing the W8A8 quantization check. While this enables the feature for more models, it introduces a critical issue. The change allows non-quantized models to use a communication path (FusedMC2CommImpl) that strictly requires quantization scales, which will lead to a runtime crash. My review includes a critical comment detailing the issue and suggesting a path forward to correctly and safely implement this feature.

[github-actions]

This pull request has conflicts, please resolve those before we can evaluate the pull request.

[github-actions]

This pull request has conflicts, please resolve those before we can evaluate the pull request.

[github-actions]

This pull request has conflicts, please resolve those before we can evaluate the pull request.

[github-actions]

This pull request has conflicts, please resolve those before we can evaluate the pull request.

[MengqingCao]

Could you add a test case for this scenario?

[MengqingCao]

LGTM now, thanks!