[main] Use AddRmsNormQuant ops in the custom model to optimize Qwen3's performance (#1806)

### What this PR does / why we need it?
Optimizes the performance of the Qwen3 quantization model by registering
a custom model and adding the AddRmsNormQuant operation. Subsequent PRs
will focus on performance optimizations based on this custom model.

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

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

- vLLM version: v0.9.2
- vLLM main:
8d0a01a5f2

Signed-off-by: rjg-lyh <1318825571@qq.com>

vllm_ascend/models/__init__.py

@@ -11,6 +11,7 @@ def register_model():
     from .qwen2_5_vl import \
         AscendQwen2_5_VLForConditionalGeneration  # noqa: F401
     from .qwen2_vl import AscendQwen2VLForConditionalGeneration  # noqa: F401
+    from .qwen3 import CustomQwen3ForCausalLM  # noqa: F401
 
     ModelRegistry.register_model(
         "DeepSeekMTPModel",
@@ -53,6 +54,9 @@ def register_model():
         "Qwen3MoeForCausalLM",
         "vllm_ascend.models.qwen3_moe:CustomQwen3MoeForCausalLM")
 
+    ModelRegistry.register_model(
+        "Qwen3ForCausalLM", "vllm_ascend.models.qwen3:CustomQwen3ForCausalLM")
+
     ModelRegistry.register_model(
         "PanguProMoEForCausalLM",
-        "vllm_ascend.models.pangu_moe:PanguProMoEForCausalLM")
+        "vllm_ascend.models.pangu_moe:PanguProMoEForCausalLM")