renew

models/roma_unsb_model.py

@@ -97,9 +97,13 @@ class ContentAwareOptimization(nn.Module):
         cosine_fake = self.compute_cosine_similarity(gradients_fake)
         
         # 生成权重图（与原代码相同）
-        k = int(self.eta_ratio * N)
+        k = int(self.eta_ratio * cosine_fake.shape[1])
+        _, fake_indices = torch.topk(-cosine_fake, k, dim=1)
         weight_fake = torch.ones_like(cosine_fake)
 
+        for b in range(cosine_fake.shape[0]):
+            weight_fake[b, fake_indices[b]] = self.lambda_inc / (1e-6 + torch.abs(cosine_fake[b, fake_indices[b]]))    
+
         # 重建空间维度 --------------------------------------------------
         # 将权重从[B, N]转换为[B, H, W]
         weight_fake = weight_fake.view(-1, H, W).unsqueeze(1) # [B,1,H,W]