save wer/cer and avg_loss during training

train.py

@@ -318,16 +318,16 @@ def main():
  cer = total_cer / len(test_loader.dataset)
  wer *= 100
  cer *= 100
-
+ loss_results[epoch] = avg_loss
+ wer_results[epoch] = wer
+ cer_results[epoch] = cer
  print('Validation Summary Epoch: [{0}]\t'
  'Average WER {wer:.3f}\t'
  'Average CER {cer:.3f}\t'.format(
  epoch + 1, wer=wer, cer=cer))
 
  if args.visdom:
- loss_results[epoch] = avg_loss
- wer_results[epoch] = wer
- cer_results[epoch] = cer
+
  # epoch += 1
  x_axis = epochs[0:epoch + 1]
  y_axis = [loss_results[0:epoch + 1], wer_results[0:epoch + 1], cer_results[0:epoch + 1]]
@@ -346,9 +346,6 @@ def main():
  update='replace',
  )
  if args.tensorboard:
- loss_results[epoch] = avg_loss
- wer_results[epoch] = wer
- cer_results[epoch] = cer
  info = {
  'Avg Train Loss': avg_loss,
  'Avg WER': wer,