code: def train_step(self, model, samples):
      output = model(samples)
      loss_dict = {}
      for k, v in output.items():
          if "loss" in k:
              loss_dict[k] = v
      return output["loss"], loss_dict
  
imports: import logging
  import os
  import torch
  import torch.distributed
  from lavis.common.dist_utils import get_rank, get_world_size, is_main_process, is_dist_avail_and_initialized
  from lavis.common.logger import MetricLogger, SmoothedValue
  from lavis.common.registry import registry
  from lavis.datasets.data_utils import prepare_sample
label_desc: Use image node_id 5 for calling the BaseTask obj's underlying member method code with example usage: obj.train_step(model, samples) and returns: output,  loss_dict