From 5bd7a08877fe19944b28738f47b96aa684492cf7 Mon Sep 17 00:00:00 2001
From: Disty0 <disty@disty.xyz>
Date: Tue, 10 Jun 2025 03:29:07 +0300
Subject: [PATCH] don't use inplace ops in quant layer

---
 modules/sdnq/__init__.py | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/modules/sdnq/__init__.py b/modules/sdnq/__init__.py
index fde0b2a26..345045da9 100644
--- a/modules/sdnq/__init__.py
+++ b/modules/sdnq/__init__.py
@@ -123,14 +123,10 @@ def sdnq_quantize_layer(layer, weights_dtype="int8", torch_dtype=None, group_siz
 
         if dtype_dict[weights_dtype]["is_unsigned"]:
             scale, zero_point = get_scale_asymmetric(layer.weight, reduction_axes, weights_dtype)
-            layer.weight.data.sub_(zero_point).div_(scale)
         else:
             scale = get_scale_symmetric(layer.weight, reduction_axes, weights_dtype)
-            layer.weight.data.div_(scale)
             zero_point = None
-        if dtype_dict[weights_dtype]["is_integer"]:
-            layer.weight.data.round_()
-        layer.weight.data = layer.weight.data.clamp_(dtype_dict[weights_dtype]["min"], dtype_dict[weights_dtype]["max"]).to(dtype_dict[weights_dtype]["torch_dtype"])
+        layer.weight.data = quantize_weight(layer.weight, scale, zero_point, weights_dtype)
 
         if not shared.opts.sdnq_decompress_fp32 and not (use_quantized_matmul and not dtype_dict[weights_dtype]["is_integer"] and not use_tensorwise_fp8_matmul):
             scale = scale.to(torch_dtype)
@@ -214,6 +210,17 @@ def get_scale_symmetric(weight: torch.FloatTensor, reduction_axes: List[int], we
     return scale
 
 
+def quantize_weight(weight: torch.FloatTensor, scale: torch.FloatTensor, zero_point: torch.FloatTensor, weights_dtype: str) -> torch.Tensor:
+    if zero_point is not None:
+        compressed_weight = torch.sub(weight, zero_point).div_(scale)
+    else:
+        compressed_weight = torch.div(weight, scale)
+    if dtype_dict[weights_dtype]["is_integer"]:
+        compressed_weight.round_()
+    compressed_weight = compressed_weight.clamp_(dtype_dict[weights_dtype]["min"], dtype_dict[weights_dtype]["max"]).to(dtype_dict[weights_dtype]["torch_dtype"])
+    return compressed_weight
+
+
 class QuantizationMethod(str, Enum):
     SDNQ = "sdnq"