aining
              prev_step, model_file = self.get_saved_model_info()
              self.load_model(model_file)
          else:
              prev_step = 0
          
          <b>output_model_file_name = os.path.join(conf.cachedir,'deepnet-{}')</b>
          train_info_dict = {'step':[],'train_loss':[]}
          
          for step in range(prev_step,conf.dl_steps):
              img, labels = next(data_loader) 
              # For TF based networks, the whole dataset pipeline needs to be setup appropr