fix nz for quantization

Signed-off-by: wangxiyuan <[email protected]>

Author: wangxiyuan

vllm_ascend/quantization/w4a8_dynamic.py

@@ -27,7 +27,7 @@
 from vllm_ascend.ascend_config import get_ascend_config
 from vllm_ascend.distributed.parallel_state import get_mc2_group
 from vllm_ascend.ops.moe.experts_selector import select_experts
-from vllm_ascend.utils import ACL_FORMAT_FRACTAL_NZ, is_enable_nz
+from vllm_ascend.utils import ACL_FORMAT_FRACTAL_NZ
 
 
 class AscendW4A8DynamicLinearMethod:
@@ -482,10 +482,9 @@ def process_weights_after_loading(self, layer):
 
         self.update_bias(layer, w13_bias, w2_bias)
 
-        if is_enable_nz():
-            layer.w13_weight.data = torch_npu.npu_format_cast(
-                layer.w13_weight.data, ACL_FORMAT_FRACTAL_NZ)
-            layer.w2_weight.data = torch_npu.npu_format_cast(
-                layer.w2_weight.data, ACL_FORMAT_FRACTAL_NZ)
+        layer.w13_weight.data = torch_npu.npu_format_cast(
+            layer.w13_weight.data, ACL_FORMAT_FRACTAL_NZ)
+        layer.w2_weight.data = torch_npu.npu_format_cast(
+            layer.w2_weight.data, ACL_FORMAT_FRACTAL_NZ)
         layer.w13_weight.data = self.pack_to_int32(layer.w13_weight.data)
         layer.w2_weight.data = self.pack_to_int32(layer.w2_weight.data)

vllm_ascend/quantization/w8a8.py

@@ -347,7 +347,7 @@ def process_weights_after_loading(self, layer):
         # converting ACL_FORMAT_FRACTAL_NZ.
         # npu_quant_grouped_matmul_dequant in eager mode does not accept
         # ACL_FORMAT_FRACTAL_NZ.
-        if not is_310p() and is_enable_nz():
+        if not is_310p():
             layer.w13_weight.data = torch_npu.npu_format_cast(
                 layer.w13_weight.data, ACL_FORMAT_FRACTAL_NZ).contiguous()
             layer.w2_weight.data = torch_npu.npu_format_cast(

vllm_ascend/quantization/w8a8_dynamic.py

@@ -270,9 +270,8 @@ def process_weights_after_loading(self, layer):
                 1, 2).contiguous()
             layer.w2_weight.data = layer.w2_weight.data.transpose(
                 1, 2).contiguous()
-        if is_enable_nz():
-            torch_npu.npu_format_cast_(layer.w13_weight, ACL_FORMAT_FRACTAL_NZ)
-            torch_npu.npu_format_cast_(layer.w2_weight, ACL_FORMAT_FRACTAL_NZ)
+        torch_npu.npu_format_cast_(layer.w13_weight, ACL_FORMAT_FRACTAL_NZ)
+        torch_npu.npu_format_cast_(layer.w2_weight, ACL_FORMAT_FRACTAL_NZ)
         layer.w13_weight_scale.data = layer.w13_weight_scale.data.view(
             layer.w13_weight_scale.data.shape[0], -1)
         layer.w13_weight_scale_fp32 = layer.w13_weight_scale.data.to(