code: def train(self, start_epoch=1, num_epochs=1):
      self.initialize_dataloader()
      for self.epoch in range(start_epoch, num_epochs + 1):
          self.set_to_train()
          c_f.LOGGER.info("TRAINING EPOCH %d" % self.epoch)
          pbar = tqdm.tqdm(range(self.iterations_per_epoch))
          for self.iteration in pbar:
              self.forward_and_backward()
              self.end_of_iteration_hook(self)
              pbar.set_description(
                  "total_loss=%.5f" % self.losses["total_loss"]
              )
              self.step_lr_schedulers(end_of_epoch=False)
          self.step_lr_schedulers(end_of_epoch=True)
          self.zero_losses()
          if self.end_of_epoch_hook(self) is False:
              break
  
imports: import torch
  import tqdm
  from ..utils import common_functions
  from ..utils import loss_tracker
  from ..utils.key_checker import KeyChecker, KeyCheckerDict
label_desc: Use image node_id 5 for calling the BaseTrainer obj's underlying member method code with example usage: obj.train(start_epoch, num_epochs) without return types