update

examples/nx_clean_unet/step_2_train_model.py

@@ -288,7 +288,8 @@ def main():
             metric_g = discriminator.forward(clean_audios, audio_g.detach())
             loss_metric = F.mse_loss(metric_g.flatten(), one_labels)
 
-            loss_gen_all = loss_mag * 0.9 + loss_pha * 0.3  + loss_com * 0.1 + loss_metric * 0.05 + loss_time * 0.2
+            # loss_gen_all = loss_mag * 0.9 + loss_pha * 0.3  + loss_com * 0.1 + loss_metric * 0.05 + loss_time * 0.2
+            loss_gen_all = loss_mag * 0.1 + loss_pha * 0.1  + loss_com * 0.1 + loss_metric * 0.9 + loss_time * 0.9
 
             loss_gen_all.backward()
             optim_g.step()