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[main] addrmsnorm + quant fusion optim in Dense Models (#2772)

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### What this PR does / why we need it?
This PR fused addrmsnorm op and w8a8 quant op to get better perf.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
CI passed with new added/existing test.

- vLLM version: v0.10.2
- vLLM main:
0faf3cc3e8

Signed-off-by: rjg-lyh <1318825571@qq.com>
This commit is contained in:
rjg-lyh
2025-09-16 22:31:38 +08:00
committed by GitHub
parent 88ca8a051c
commit 6b7117dbb7
5 changed files with 211 additions and 270 deletions
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3
vllm_ascend/models/__init__.py
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@@ -35,9 +35,6 @@ def register_model():
"Qwen3MoeForCausalLM",
"vllm_ascend.models.qwen3_moe:CustomQwen3MoeForCausalLM")
ModelRegistry.register_model(
"Qwen3ForCausalLM", "vllm_ascend.models.qwen3:CustomQwen3ForCausalLM")
# There is no PanguProMoEForCausalLM in vLLM, so we should register it before vLLM config initialization
# to make sure the model can be loaded correctly. This register step can be removed once vLLM support PanguProMoEForCausalLM.
ModelRegistry.register_model(