update

examples/mpnet_aishell/step_2_train_model.py

@@ -212,7 +212,7 @@ def main():
             clean_audio, noisy_audio = batch
             clean_audio = clean_audio.to(device)
             noisy_audio = noisy_audio.to(device)
-            one_labels = torch.ones(config.batch_size).to(device)
+            one_labels = torch.ones(clean_audio.shape[0]).to(device)
 
             clean_mag, clean_pha, clean_com = mag_pha_stft(clean_audio, config.n_fft, config.hop_size, config.win_size, config.compress_factor)
             noisy_mag, noisy_pha, noisy_com = mag_pha_stft(noisy_audio, config.n_fft, config.hop_size, config.win_size, config.compress_factor)
@@ -234,7 +234,7 @@ def main():
             if batch_pesq_score is not None:
                 loss_disc_g = F.mse_loss(batch_pesq_score.to(device), metric_g.flatten())
             else:
-                print("pesq is None!")
+                # print("pesq is None!")
                 loss_disc_g = 0
 
             loss_disc_all = loss_disc_r + loss_disc_g