init

model_pyannote_embedding.py

@@ -21,7 +21,7 @@ class PyannoteSE:
         self.inference = Inference(model, window="whole")
 
     def get_speaker_embedding(self, wav: np.ndarray, sampling_rate: Optional[int] = None) -> np.ndarray:
-        wav = torch.as_tensor(wav.reshape(1, -1)).to(self.device)
+        wav = torch.as_tensor(wav.reshape(1, -1), dtype=torch.float32).to(self.device)
         fix_reproducibility(self.inference.device)
         if self.inference.window == "sliding":
             return self.inference.slide(wav, sampling_rate, hook=None)