[feature]Ascend quantization support (#7791)

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

python/sglang/srt/layers/linear.py

@@ -34,6 +34,7 @@ from sglang.srt.layers.quantization.base_config import (
 from sglang.srt.utils import (
     cpu_has_amx_support,
     is_cpu,
+    is_npu,
     set_weight_attrs,
     use_intel_amx_backend,
 )
@@ -60,6 +61,7 @@ WEIGHT_LOADER_V2_SUPPORTED = [
 
 _is_cpu_amx_available = cpu_has_amx_support()
 _is_cpu = is_cpu()
+_is_npu = is_npu()
 
 
 def adjust_marlin_shard(param, shard_size, shard_offset):
@@ -297,6 +299,14 @@ class ReplicatedLinear(LinearBase):
         if len(loaded_weight.shape) == 0:
             loaded_weight = loaded_weight.reshape(1)
 
+        # The per-tensor quant-scale must be 1 dimension
+        if _is_npu:
+            if param.size() != loaded_weight.size() and param.size(0) == 1:
+                if torch.allclose(loaded_weight, loaded_weight[0]):
+                    loaded_weight = loaded_weight[:1]
+                else:
+                    raise ValueError(f"{loaded_weight} are not all equal")
+
         assert param.size() == loaded_weight.size()
         param.data.copy_(loaded_weight)