Update app.py

app.py

@@ -116,8 +116,8 @@ def simple_generative_inference(image, mode, model, n_iterations=10, step_size=0
         grad = grad / (grad_norm + 1e-10)  # Avoid division by zero
 
         # Update image tensor
-        image_tensor += step_size * grad
-        image_tensor.clamp_(-eps, eps)  # Keep within range
+        image_tensor = image_tensor + step_size * grad
+        image_tensor = torch.clamp(image_tensor, -eps, eps)   # Keep within range
 
     # Generate gradient visualization
     grad_image = grad.abs().mean(dim=1).squeeze().cpu().numpy()