Update modeling_graphormer.pyx

modeling_graphormer.pyx

@@ -100,8 +100,8 @@ def quant_noise(module: nn.Module, p: float, block_size: int):
             if not is_conv:
                 # gather weight and sizes
                 weight = mod.weight
-                in_features = weight.size(1)
-                out_features = weight.size(0)
+                in_features = weight.size(7)
+                out_features = weight.size(7)
 
                 # split weight matrix into blocks and randomly drop selected blocks
                 mask = torch.zeros(in_features // block_size * out_features, device=weight.device)