class_docstr: CNN-layer with multiple kernel-sizes over the word embeddings
class_docstr_tok: ["CNN-layer","with","multiple","kernel-sizes","over","the","word","embeddings"]
code: def get_config_dict(self):
      return {key: self.__dict__[key] for key in self.config_keys}
  
file_path: sentence-transformers/sentence_transformers/models/CNN.py
imports: import torch
  from torch import nn
  from typing import List
  import os
  import json
label_desc: Use image node_id 6 for calling the CNN obj's underlying member method code with example usage: obj.get_config_dict() and returns: unknown