code: def test_set_training_config(
      self, model_sample, train_dataset, training_configs
  ):
      trainer = BaseTrainer(
          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 == BaseTrainerConfig(
              output_dir="dummy_output_dir", keep_best_on_train=True
          )
  
      else:
          assert trainer.training_config == training_configs
  
imports: import os
  from copy import deepcopy
  import pytest
  import torch
  from pythae.customexception import ModelError
  from pythae.models import AE, RHVAE, VAE, AEConfig, RHVAEConfig, VAEConfig
  from pythae.trainers import BaseTrainer, BaseTrainerConfig
  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