bug fix

train.py

@@ -144,7 +144,7 @@ def train(model, criterion, data_loader, optimizer, epoch):
         progbar_display['total_loss'] =  loss.item()
         progbar_display['linear_loss'] = linear_loss.item()
         progbar_display['mel_loss'] = mel_loss.item()
-        progbar_display['grad_norm'] = grad_norm
+        progbar_display['grad_norm'] = grad_norm.item()
 
         # update
         progbar.update(num_iter+1, values=list(progbar_display.items()))

utils/generic_utils.py

@@ -113,7 +113,7 @@ def save_best_model(model, optimizer, model_loss, best_loss, out_path,
 def check_update(model, grad_clip, grad_top):
     r'''Check model gradient against unexpected jumps and failures'''
     skip_flag = False
-    grad_norm = torch.nn.utils.clip_grad_norm(model.parameters(), grad_clip)
+    grad_norm = torch.nn.utils.clip_grad_norm_(model.parameters(), grad_clip)
     if np.isinf(grad_norm):
         print(" | > Gradient is INF !!")
         skip_flag = True