update

examples/nx_clean_unet/step_2_train_model.py

@@ -250,8 +250,8 @@ def main():
 
             clean_audio_list = torch.split(clean_audios, 1, dim=0)
             enhanced_audio_list = torch.split(audio_g, 1, dim=0)
-            clean_audio_list = [t.squeeze().cpu().numpy() for t in clean_audio_list]
-            enhanced_audio_list = [t.squeeze().cpu().numpy() for t in enhanced_audio_list]
+            clean_audio_list = [t.squeeze().detach().cpu().numpy() for t in clean_audio_list]
+            enhanced_audio_list = [t.squeeze().detach().cpu().numpy() for t in enhanced_audio_list]
 
             pesq_score_list: List[float] = run_batch_pesq(clean_audio_list, enhanced_audio_list, sample_rate=config.sample_rate, mode="nb")