[main] Fuse GroupedMatmul, Swiglu and DynamicQuant in W8A8_DYNAMIC quantized MoE layers

[zhoux77899]

What this PR does / why we need it?

Does this PR introduce any user-facing change?

How was this patch tested?

Tested on W8A8 quantized Qwen3-235B-A22B model with bs=16

1. tp=8, dp=1, moe_tp=8, moe_ep=1, TPOP increased 21.54%, Output Token Throughput increased 27.35%

2. tp=8, dp=1, moe_tp=1, moe_ep=8, TPOP increased 17.38%, Output Token Throughput increased 6.86%

• vLLM version: v0.10.0
• vLLM main: vllm-project/vllm@3821787

[github-actions]

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[codecov]

Codecov Report

❌ Patch coverage is 83.73494% with 27 lines in your changes missing coverage. Please review.
✅ Project coverage is 77.92%. Comparing base (1de16ea) to head (90ea998).

Files with missing lines	Patch %	Lines
vllm_ascend/quantization/w8a8_dynamic.py	43.33%	17 Missing ⚠️
vllm_ascend/quantization/w4a8_dynamic.py	70.58%	10 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2275      +/-   ##
==========================================
+ Coverage   77.37%   77.92%   +0.54%     
==========================================
  Files         128      128              
  Lines       16455    16608     +153     
==========================================
+ Hits        12732    12941     +209     
+ Misses       3723     3667      -56     

Flag	Coverage Δ
unittests	77.92% <83.73%> (+0.54%)	⬆️

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[github-actions]

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

[realliujiaxu]

need to modify fused_experts_with_mc2(): pass expert_token_nums_type=1 to npu_moe_distribute_dispatch() and pass group_list_type = 0 to apply_mlp_decode()

[github-actions]

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