deviec type autocast

notebook.ipynb

@@ -91,7 +91,7 @@
     "            audio_tensor = torch.tensor(audio).float().unsqueeze(0).to(device)\n",
     "            \n",
     "            # Extract features\n",
-    "            with torch.no_grad():\n",
+    "            with torch.no_grad(),torch.autocast(device_type='cuda'):\n",
     "                features = model.encode(audio_tensor)\n",
     "                if isinstance(features, dict):\n",
     "                    for key in ['last_hidden_state', 'embeddings', 'audio']:\n",
@@ -271,4 +271,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}