code: def __init__(
      self,
      num_classes,
      pretrained=True,
      checkpoints=None,
      mode="base",
      **kwargs,
  ):
      super(LayoutXLMForSer, self).__init__(
          LayoutXLMModel,
          LayoutXLMForTokenClassification,
          mode,
          "ser",
          pretrained,
          checkpoints,
          num_classes=num_classes,
      )
      if (
          hasattr(self.model.layoutxlm, "use_visual_backbone")
          and self.model.layoutxlm.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 LayoutXLMForSer object from inherited base classes: NLPBaseModel with example: obj = LayoutXLMForSer(num_classes, pretrained, checkpoints, mode)