[Feat]Qwen3 Moe supports npu_add_rms_norm_quant op by default, update op with norm bias (#3205)

### What this PR does / why we need it?
1. qwen3 moe uses add_rms_norm_quant op instead of 'add_rms_norm op and
quant op' during quantization scene.
2. torch_npu.add_rms_norm_quant op fixed accuracy while model weights is
quantized by anti_method m4, m4 quantization is asymmetric outlier
suppression method, it will generate none-zero norm bias,
add_rms_norm_quant op updated to add this parameter to calculate.

### Does this PR introduce _any_ user-facing change?
please use a torch_npu version >= torch_npu-2.7.1.dev20250919

### How was this patch tested?
1. no special parameters to set, no new envs to set.
2. use qwen3 moe quantization model to test ,such as
Qwen3-235B-A22B-W8A8, Qwen3-30B-A3B-W8A8,
Qwen3-235B-A22B-Instruct-2507-m4 (anti_method m4)

- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: huangdong2022 <huangdong51@huawei.com>
Signed-off-by: h30027576 <huangdong51@huawei.com>

vllm_ascend/utils.py

@@ -505,8 +505,7 @@ def register_ascend_customop(vllm_config: Optional[VllmConfig] = None):
     from vllm_ascend.ops.activation import AscendQuickGELU, AscendSiluAndMul
     from vllm_ascend.ops.common_fused_moe import (AscendFusedMoE,
                                                   AscendSharedFusedMoE)
-    from vllm_ascend.ops.layernorm import (AscendGemmaRMSNorm,
-                                           AscendQuantRMSNorm, AscendRMSNorm)
+    from vllm_ascend.ops.layernorm import AscendGemmaRMSNorm, AscendRMSNorm
     from vllm_ascend.ops.linear import (AscendColumnParallelLinear,
                                         AscendMergedColumnParallelLinear,
                                         AscendQKVParallelLinear,
@@ -537,11 +536,6 @@ def register_ascend_customop(vllm_config: Optional[VllmConfig] = None):
         "MultiHeadLatentAttention": AscendMultiHeadLatentAttention,
     }
 
-    if vllm_config is not None and \
-        vllm_config.quant_config is not None and \
-        any("norm.bias" in name for name in vllm_config.quant_config.quant_description.keys()):
-        REGISTERED_ASCEND_OPS["RMSNorm"] = AscendQuantRMSNorm
-
     for name, op_cls in REGISTERED_ASCEND_OPS.items():
         CustomOp.register_oot(_decorated_op_cls=op_cls, name=name)