[3/N][Refactor][Quantization]remove packed_modules_mapping from models (#3021)

### What this PR does / why we need it?

Some custom models in vllm-ascend define packed_modules_mapping, which
prevent keeping same model class with vllm community. So move these
custom packed_modules_mapping to quant utils.py. After this pr, some
custom models can be removed.

### Does this PR introduce _any_ user-facing change?

tested by CI

### How was this patch tested?

tested by CI

- vLLM version: v0.10.2
- vLLM main:
5089fd749c

Signed-off-by: 22dimensions <waitingwind@foxmail.com>

vllm_ascend/quantization/quant_config.py

@@ -19,6 +19,7 @@ from types import MappingProxyType
 from typing import Any, Callable, Dict, List, Mapping, Optional
 
 import torch
+from vllm.config import get_current_vllm_config
 from vllm.distributed import get_tensor_model_parallel_rank
 from vllm.model_executor.layers.fused_moe import (FusedMoE, FusedMoEMethodBase,
                                                   FusedMoeWeightScaleSupported)
@@ -89,6 +90,11 @@ class AscendQuantConfig(QuantizationConfig):
 
     def get_quant_method(self, layer: torch.nn.Module,
                          prefix: str) -> Optional["QuantizeMethodBase"]:
+        vllm_config = get_current_vllm_config()
+        model_type = vllm_config.model_config.hf_config.model_type
+        if model_type in packed_modules_model_mapping:
+            self.packed_modules_mapping = packed_modules_model_mapping[
+                model_type]
         from vllm.attention.layer import Attention
         if prefix.startswith("language_model"):
             prefix = prefix.split('.', 1)[-1]
@@ -153,6 +159,61 @@ class AscendQuantConfig(QuantizationConfig):
         return []
 
 
+packed_modules_model_mapping = {
+    "qwen3_moe": {
+        "qkv_proj": [
+            "q_proj",
+            "k_proj",
+            "v_proj",
+        ],
+        "gate_up_proj": [
+            "gate_proj",
+            "up_proj",
+        ],
+        "experts":
+        ["experts.0.gate_proj", "experts.0.up_proj", "experts.0.down_proj"],
+    },
+    "deepseek_v2": {
+        "gate_up_proj": ["gate_proj", "up_proj"],
+        "experts":
+        ["experts.0.gate_proj", "experts.0.up_proj", "experts.0.down_proj"]
+    },
+    "deepseek_v3": {
+        "gate_up_proj": ["gate_proj", "up_proj"],
+        "experts":
+        ["experts.0.gate_proj", "experts.0.up_proj", "experts.0.down_proj"]
+    },
+    # NOTE 1.The quantized MTP layer of deepseek on the NPU is not quantized;
+    # NOTE 2.The description file generated by the current msmodelslim tool does not have
+    # MTP layer info. Please manually add it and set the value to FLOAT.
+    "deepseek_mtp": {
+        "gate_up_proj": ["gate_proj", "up_proj"],
+        "experts":
+        ["experts.0.gate_proj", "experts.0.up_proj", "experts.0.down_proj"]
+    },
+    "qwen3_next": {
+        "qkv_proj": [
+            "q_proj",
+            "k_proj",
+            "v_proj",
+        ],
+        "gate_up_proj": ["gate_proj", "up_proj"],
+        "in_proj": ["in_proj_qkvz", "in_proj_ba"],
+    },
+    "qwen2_5_vl": {
+        "qkv_proj": [
+            "q_proj",
+            "k_proj",
+            "v_proj",
+        ],
+        "gate_up_proj": [
+            "gate_proj",
+            "up_proj",
+        ],
+    }
+}
+
+
 class AscendLinearMethod(LinearMethodBase):
     """Linear method for Ascend quantization.