class_docstr: BertEmbedding is a simple wrapped class of TransformerEmbedding.
  If you need load other kind of transformer based language model, please use the TransformerEmbedding.
code: def to_dict(self) -> Dict[str, Any]:
      info_dic = super(BertEmbedding, self).to_dict()
      info_dic["config"]["model_folder"] = self.model_folder
      return info_dic
  
imports: import os
  from typing import Dict, Any
  from kashgari.embeddings.transformer_embedding import TransformerEmbedding
label_desc: Use image node_id 1 for calling the BertEmbedding obj's underlying member method code with example usage: obj.to_dict() and returns: info_dic