code: def configs_and_models(self, tmpdir, request):
      tmpdir.mkdir("dummy_folder")
      dir_path = os.path.join(tmpdir, "dummy_folder")
      request.param[1].output_dir = dir_path
  
      if request.param[0].name == "AEConfig":
          model = AE(request.param[0])
      elif request.param[0].name == "RAE_L2_Config":
          model = RAE_L2(request.param[0])
      elif request.param[0].name == "Adversarial_AE_Config":
          model = Adversarial_AE(request.param[0])
      else:
          model = VAEGAN(request.param[0])
  
      return [model, request.param[1]]
  
imports: import os
  from collections import Counter
  import pytest
  import torch
  from pythae.models import AE, RAE_L2, VAEGAN, Adversarial_AE, Adversarial_AE_Config, AEConfig, RAE_L2_Config, VAEGANConfig
  from pythae.trainers import *
  from pythae.trainers.training_callbacks import *
label_desc: Use image node_id 2 for calling the Test_TrainersCalls obj's underlying member method code with example usage: obj.configs_and_models(tmpdir, request) and returns: list