code: def __init__(
      self, pretrained=True, checkpoints=None, mode="base", **kwargs
  ):
      super(LayoutLMv2ForRe, self).__init__(
          LayoutLMv2Model,
          LayoutLMv2ForRelationExtraction,
          mode,
          "re",
          pretrained,
          checkpoints,
      )
      if (
          hasattr(self.model.layoutlmv2, "use_visual_backbone")
          and self.model.layoutlmv2.use_visual_backbone is False
      ):
          self.use_visual_backbone = False
  
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 1 to create a new LayoutLMv2ForRe object from inherited base classes: NLPBaseModel with example: obj = LayoutLMv2ForRe(pretrained, checkpoints, mode)