[feature]Ascend quantization support (#7791)

Co-authored-by: ichernob <ichernobnn@gmail.com>
Co-authored-by: liupeng <liupeng374@huawei.com>

python/sglang/srt/model_loader/loader.py

@@ -64,10 +64,13 @@ from sglang.srt.model_loader.weight_utils import (
 from sglang.srt.utils import (
     get_bool_env_var,
     get_device_capability,
+    is_npu,
     is_pin_memory_available,
     set_weight_attrs,
 )
 
+_is_npu = is_npu()
+
 
 @contextmanager
 def device_loading_context(module: torch.nn.Module, target_device: torch.device):
@@ -127,18 +130,19 @@ def _get_quantization_config(
         # (yizhang2077) workaround for nvidia/Llama-4-Maverick-17B-128E-Eagle3
         if quant_config is None:
             return None
-        major, minor = get_device_capability()
+        if not _is_npu:
+            major, minor = get_device_capability()
 
-        if major is not None and minor is not None:
-            assert 0 <= minor < 10
-            capability = major * 10 + minor
-            if capability < quant_config.get_min_capability():
-                raise ValueError(
-                    f"The quantization method {model_config.quantization} "
-                    "is not supported for the current GPU. "
-                    f"Minimum capability: {quant_config.get_min_capability()}. "
-                    f"Current capability: {capability}."
-                )
+            if major is not None and minor is not None:
+                assert 0 <= minor < 10
+                capability = major * 10 + minor
+                if capability < quant_config.get_min_capability():
+                    raise ValueError(
+                        f"The quantization method {model_config.quantization} "
+                        "is not supported for the current GPU. "
+                        f"Minimum capability: {quant_config.get_min_capability()}. "
+                        f"Current capability: {capability}."
+                    )
         supported_dtypes = quant_config.get_supported_act_dtypes()
         if model_config.dtype not in supported_dtypes:
             raise ValueError(
@@ -157,6 +161,13 @@ def _initialize_model(
     """Initialize a model with the given configurations."""
     model_class, _ = get_model_architecture(model_config)
     packed_modules_mapping = getattr(model_class, "packed_modules_mapping", {})
+    if _is_npu:
+        packed_modules_mapping["fused_qkv_a_proj_with_mqa"] = [
+            "q_a_proj",
+            "kv_a_proj_with_mqa",
+        ]
+        packed_modules_mapping["qkv_proj"] = ["q_proj", "k_proj", "v_proj"]
+        packed_modules_mapping["gate_up_proj"] = ["gate_proj", "up_proj"]
     quant_config = _get_quantization_config(
         model_config, load_config, packed_modules_mapping
     )