code: def test_update_transformer_module_keys():
      state_dict_with_old_keys = {
          "input_features.module_dict.sentence__ludwig.encoder_obj.transformer.embeddings.LayerNorm.bias": 0.0,
          "sentence__ludwig.encoder_obj.transformer.encoder.layer.0.attention.output.LayerNorm.weight": 0.0,
          "module_dict.sentence__ludwig.encoder_obj.transformer.embeddings.word_embeddings.weight": 0.0,
      }
  
      expected_state_dict = {
          "input_features.module_dict.sentence__ludwig.encoder_obj.transformer.module.embeddings.LayerNorm.bias": 0.0,
          "sentence__ludwig.encoder_obj.transformer.module.encoder.layer.0.attention.output.LayerNorm.weight": 0.0,
          "module_dict.sentence__ludwig.encoder_obj.transformer.module.embeddings.word_embeddings.weight": 0.0,
      }
  
      # Ensures that, for models saved before FreezeModule was added, 'module' is added to the key path.
      updated_state_dict = update_state_dict(state_dict_with_old_keys)
      assert updated_state_dict == expected_state_dict
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_update_transformer_module_keys() without return types