add eval() before inference

pytorch/model.py

@@ -41,6 +41,7 @@ class Model():
         self._model.eval()
 
     def __call__(self, img_tensor: torch.Tensor):
+        self._model.eval()
         features = self._model.forward_features(img_tensor)
         if features.dim() == 4:  # if the shape of feature map is [N, C, H, W], where H > 1 and W > 1
             global_pool = nn.AdaptiveAvgPool2d(1)