code: def forward(self, x):
      if self.use_visual_backbone is True:
          image = x[4]
      else:
          image = None
      x = self.model(
          input_ids=x[0],
          bbox=x[1],
          attention_mask=x[2],
          token_type_ids=x[3],
          image=image,
          position_ids=None,
          head_mask=None,
          labels=None,
      )
      if self.training:
          res = {"backbone_out": x[0]}
          res.update(x[1])
          return res
      else:
          return x
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from paddle import nn
  from paddlenlp.transformers import LayoutXLMModel, LayoutXLMForTokenClassification, LayoutXLMForRelationExtraction
  from paddlenlp.transformers import LayoutLMModel, LayoutLMForTokenClassification
  from paddlenlp.transformers import LayoutLMv2Model, LayoutLMv2ForTokenClassification, LayoutLMv2ForRelationExtraction
  from paddlenlp.transformers import AutoModel
label_desc: Use image node_id 2 for calling the LayoutXLMForSer obj's underlying member method code with example usage: obj.forward(x) and returns: res, x