Update lora_w2w.py

lora_w2w.py

@@ -82,8 +82,8 @@ class LoRAModule(nn.Module):
         if type(alpha) == torch.Tensor:
             alpha = alpha.detach().numpy()
         alpha = lora_dim if alpha is None or alpha == 0 else alpha
-        self.scale = alpha / self.lora_dim
-        self.scale = self.scale.bfloat16()
+        # self.scale = alpha / self.lora_dim
+        # self.scale = self.scale.bfloat16()
         
 
         self.multiplier = multiplier
@@ -95,11 +95,10 @@ class LoRAModule(nn.Module):
         del self.org_module
 
     def forward(self, x):
-        print(self.org_forward(x).dtype)
-        print((x@(([email protected])*self.std1+self.mean1).T).dtype)
+       
 
         return self.org_forward(x) +\
-            (x@(([email protected])*self.std1+self.mean1).T)@((([email protected])*self.std2+self.mean2))*self.multiplier*self.scale
+            (x@(([email protected])*self.std1+self.mean1).T)@((([email protected])*self.std2+self.mean2))#*self.multiplier*self.scale