fdsfs

services/summarizer.py

@@ -10,6 +10,8 @@ model = model.eval()
 
 def get_scores(features):
     # features.shape: (N, 1024)
+    # features.dtype: torch.float32
+    # features.device: cpu
     with torch.no_grad():
         scores, _ = model(features)
     return scores.squeeze().cpu().numpy()