code: def _step(self, batch, mode="train"):
      (
          input_ids,
          token_type_ids,
          attention_mask,
          labels,
          images,
          aux_imgs,
          rcnn_imgs,
      ) = batch
      logits, loss = self.model(
          input_ids=input_ids,
          attention_mask=attention_mask,
          token_type_ids=token_type_ids,
          labels=labels,
          images=images,
          aux_imgs=aux_imgs,
          rcnn_imgs=rcnn_imgs,
      )
      return attention_mask, labels, logits, loss
  
file_path: DeepKE/src/deepke/name_entity_re/multimodal/modules/train.py
imports: import torch
  from torch import optim
  from tqdm import tqdm
  from transformers.optimization import get_linear_schedule_with_warmup
  from seqeval.metrics import classification_report
label_desc: Use image node_id 6 for calling the Trainer obj's underlying member method code with example usage: obj._step(batch, mode) and returns: attention_mask,  labels,  logits,  loss