code: def test_set_training_config(
      self, model_sample, train_dataset, training_configs
  ):
      trainer = CoupledOptimizerTrainer(
          model=model_sample,
          train_dataset=train_dataset,
          training_config=training_configs,
      )
  
      # check if default config is set
      if training_configs is None:
          assert (
              trainer.training_config
              == CoupledOptimizerTrainerConfig(
                  output_dir="dummy_output_dir"
              )
          )
  
      else:
          assert trainer.training_config == training_configs
  
imports: import os
  from copy import deepcopy
  import pytest
  import torch
  from pythae.models import RAE_L2, RAE_L2_Config
  from pythae.trainers import CoupledOptimizerTrainer, CoupledOptimizerTrainerConfig
  from tests.data.custom_architectures import *
label_desc: Use image node_id 2 for calling the Test_Set_Training_config obj's underlying member method code with example usage: obj.test_set_training_config(model_sample, train_dataset, training_configs) without return types