code: def infer_batch(self, dataloader):
          
          sum_losses = 0
          len_losses = 0
          for input_data, input_label in dataloader:
              data = gluon.utils.split_and_load(input_data, self.ctx, even_split=False)
              label = gluon.utils.split_and_load(input_label, self.ctx, even_split=False)
              sum_losses, len_losses = self.infer(data, label)
              sum_losses += sum_losses
              len_losses += len_losses
  
          return sum_losses, len_losses
docs: Description : inference for LipNet