修改YOLOX模型白盒水印嵌入流程

watermark_generate/deals/yolox_pytorch_white_embed.py

@@ -192,7 +192,7 @@ class ModelEncoder:
 
     def get_prob(self, x_random, w):
         mm = torch.mm(x_random, w.reshape((w.shape[0], 1)))
-        return F.sigmoid(mm).flatten()
+        return mm.flatten()
 
     def loss_fun(self, x, y):
         return nn.BCEWithLogitsLoss()(x, y)